• The Journal of Korean Academic Society of Nursing Education
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• v.28 no.2
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• pp.193-203
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• 2022

Purpose: This study explored the mediating role of resilience between post-traumatic stress and emotional exhaustion in nurses during the COVID-19 pandemic. Methods: The data were collected from 193 nurses working at a hospital in Daegu from October 16 to 30, 2020, in the middle of the COVID-19 pandemic. Participants conducted self-reported surveys of post-traumatic stress (Impact of Event Scale-Revised Korean version), emotional exhaustion (Maslach Burnout Inventory), and resilience (Korean Resilience Quotient Test). The data were analyzed using descriptive statistics, frequency, t-tests, Mann-Whitney U tests, Kruskal-Wallis tests, Pearson correlation coefficients, and multiple regression. Mediation analysis was performed using the Baron and Kenny method and Sobel test. Results: The mean scores for post-traumatic stress, resilience, and emotional exhaustion were 16.18±16.18, 183.41±18.29, and 32.64±9.66, respectively. A higher level of post-traumatic stress was associated with lower resilience (r=-.20, p=.004) and with higher emotional exhaustion (r=.33, p<.001). A higher level of resilience was associated with lower emotional exhaustion (r=-.35, p<.001). The resilience was confirmed to have a partial mediating effect in the relationship between post-traumatic stress and emotional exhaustion, verified by the Sobel test (Z=2.31, p=.02). Conclusion: Resilience had a partial mediating effect in the relationship between post-traumatic stress and emotional exhaustion. Thus, nurses should develop individual strengths to reduce emotional exhaustion, and managers should also make efforts to increase the nurses' resilience. It is also necessary to develop and apply a program to strengthen nurses' resilience.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.371-380
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• 2022

Convolutional neural networks are widely used to manipulate data arranged in a grid, such as images. A general convolutional neural network consists of a convolutional layers and a fully connected layers, and each layer contains a nonlinear activation functions. This paper proposes a combined parametric activation function to improve the performance of convolutional neural networks. The combined parametric activation function is created by adding the parametric activation functions to which parameters that convert the scale and location of the activation function are applied. Various nonlinear intervals can be created according to parameters that convert multiple scales and locations, and parameters can be learned in the direction of minimizing the loss function calculated by the given input data. As a result of testing the performance of the convolutional neural network using the combined parametric activation function on the MNIST, Fashion MNIST, CIFAR10 and CIFAR100 classification problems, it was confirmed that it had better performance than other activation functions.

• Steel and Composite Structures
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• v.45 no.3
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• pp.409-423
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• 2022

Nowadays, there is a high demand for great structural implementation and multifunctionality with excellent mechanical properties. The porous structures reinforced by graphene platelets (GPLs) having valuable properties, such as heat resistance, lightweight, and excellent energy absorption, have been considerably used in different engineering implementations. However, stiffness of porous structures reduces significantly, due to the internal cavities, by adding GPLs into porous medium, effective mechanical properties of the porous structure considerably enhance. This paper is relating to vibration analysis of fluidconveying cantilever porous graphene platelet reinforced (GPLR) pipe with fractional viscoelastic model resting on foundations. A dynamical model of cantilever porous GPLR pipes conveying fluid and resting on a foundation is proposed, and the vibration, natural frequencies and primary resonant of such a system are explored. The pipe body is considered to be composed of GPLR viscoelastic polymeric pipe with porosity in which Halpin-Tsai scheme in conjunction with the fractional viscoelastic model is used to govern the construction relation of nanocomposite pipe. Three different porosity distributions through the pipe thickness are introduced. The harmonic concentrated force is also applied to the pipe and the excitation frequency is close to the first natural frequency. The governing equation for transverse motions of the pipe is derived by the Hamilton principle and then discretized by the Galerkin procedure. In order to obtain the frequency-response equation, the differential equation is solved with the assumption of small displacement, damping coefficient, and excitation amplitude by the multiple scale method. A parametric sensitivity analysis is carried out to reveal the influence of different parameters, such as nanocomposite pipe properties, fluid velocity and nonlinear viscoelastic foundation coefficients, on the primary resonance and linear natural frequency. Results indicate that the GPLs weight fraction porosity coefficient, fractional derivative order and the retardation time have substantial influences on the dynamic response of the system.

• Journal of the Korean Geotechnical Society
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• v.23 no.1
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• pp.51-65
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• 2007

The purpose of this study is the development and application of a high resolution ultrasonic wave imaging system to detect discontinuity plane in lab-scale rock models. This technique is based on received time series which capture the multiple reflections at interface. This study includes the fundamental aspects of ultrasonic wave propagation in rock mass, the selection of the optimal ultrasonic wave transducer, data gathering, a signal processing, imaging methods, and experiments. Experiments are carried out by the horizontal movement and rotation devices. Experimental studies show the discontinuity is well detected by the horizontal movement and rotation devices under water. Furthermore, the discontinuity and the cavity on the plaster block are identified by the rotation device. This study suggests that the new method may be an economical and effective tool for the detection of the discontinuity on rock mass.

• Physical Therapy Korea
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• v.30 no.2
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• pp.92-101
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• 2023

Background: Stroke is one of the causes affecting gait and balance. Taping is considered an effective method for improving balance and gait in stroke patients. Numerous studies have confirmed the functional effects of taping in stroke patients. However, there is still no consensus regarding the use of taping to improve gait and balance. Objects: The purpose of this review was to investigate the effects of taping on the balance and gait of patients with stroke through meta-analysis of studies. Methods: PubMed, Medline, Embase, Web of Science, Cochrane Review, RISS, DBPia, and Science on were used to collect articles on Kinesio and non-elastic taping. The key terms were "Stroke", "Hemiplegia", "Taping", "Tape", "Balance", and "Gait" with cut-off of October, 2022. Taping group was compared with control groups with sham, placebo, and no taping. The outcome measures included the Berg Balance Scale (BBS), Timed Up and Go (TUG) test, and gait speed (cm/s). Eighteen studies (524 patients) were selected for the meta-analysis. Results: Overall, taping improved balance and gait in stroke patients, and Kinesio and non-elastic taping had similar effect sizes. Taping improved the BBS and TUG, and was most effective on gait speed. Contrary to the expectation that a longer duration of taping would be more affective, taping was most effective when the total taping duration was shorter than 500 minutes. In addition, the effect size of taping was greater when it was simultaneously attached to multiple locations. Conclusion: This meta-analysis supports the use of taping to improve gait and balance in stroke patients, and provides guidelines for the location, duration, and type of tape to increase taping efficiency.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.55.3-55.3
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• 2019

We present a pipeline to estimate baryonic properties of a galaxy inside a dark matter (DM) halo in DM-only simulations using a machine trained on high-resolution hydrodynamic simulations. As an example, we use the IllustrisTNG hydrodynamic simulation of a (75 h^-1 Mpc)³ volume to train our machine to predict e.g., stellar mass and star formation rate in a galaxy-sized halo based purely on its DM content. An extremely randomized tree (ERT) algorithm is used together with multiple novel improvements we introduce here such as a refined error function in machine training and two-stage learning. Aided by these improvements, our model demonstrates a significantly increased accuracy in predicting baryonic properties compared to prior attempts --- in other words, the machine better mimics IllustrisTNG's galaxy-halo correlation. By applying our machine to the MultiDark-Planck DM-only simulation of a large (1 h^-1 Gpc)³ volume, we then validate the pipeline that rapidly generates a galaxy catalogue from a DM halo catalogue using the correlations the machine found in IllustrisTNG. We also compare our galaxy catalogue with the ones produced by popular semi-analytic models (SAMs). Our so-called machine-assisted semi-simulation model (MSSM) is shown to be largely compatible with SAMs, and may become a promising method to transplant the baryon physics of galaxy-scale hydrodynamic calculations onto a larger-volume DM-only run. We discuss the benefits that machine-based approaches like this entail, as well as suggestions to raise the scientific potential of such approaches.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.285-294
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• 2023

As software grows continuously in scale and complexity, the role of software architecture has become increasingly important across various industries. Although software architects often rely on their experience and intuition when designing such architecture, there is a variety of methodologies being researched for architecture design. However, these methodologies do not address the specific effects of applying multiple architectural patterns to a system or the sequence in which they should be applied. In this study, we explain the variation in architectural design results depending on the order in which the same set of architectural patterns is applied to a single system. Based on this phenomenon, we identify requirements for applying architectural patterns and propose a method of classifying the patterns to be applied. We also propose a prioritization process for requirements to efficiently apply the classified patterns in a specific order. Finally, we show a case study that prioritizing requirements based on architectural pattern types is beneficial for efficient software architecture design in terms of quality attributes.

• The Journal of Korean Academic Society of Nursing Education
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• v.30 no.1
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• pp.49-60
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• 2024

Purpose: The coronavirus disease 2019 (COVID-19) pandemic has had significant physical and psychological impacts on registered nurses (RNs). This study aimed to identify long COVID symptoms and their associated factors specifically among RNs. Methods: This descriptive correlational study's sample comprised 189 nurses (31.57±5.98 years, 93.7% female) in Korea. Self-reported long COVID symptoms were assessed using the COVID-19 Yorkshire Rehabilitation Scale. Data were collected from December 31, 2022, to January 13, 2023, using the online survey method and were analyzed using independent t-test, Wilcoxon signed-rank test, one-way ANOVA, Pearson's correlation, and a multiple linear regression analysis with the IBM SPSS Statistics 26.0 program. Results: A total of 179 participants (94.7%) experienced one or more long COVID symptoms. The most prevalent symptoms were weakness (77.8%), fatigue (68.3%), breathlessness (67.7%), cough/throat sensitivity/voice change (50.3%), and sleep problems (50.3%). The factors related to long COVID symptoms were marital status, type of institution, working time, acute COVID-19 symptoms, and vaccination status. The quarantine period (β=.26, p<.001) and the nursing workforce after COVID-19 (β=-.17, p=.018) were significantly associated with long COVID symptoms (Adjusted R² =.33). Conclusion: Providing comprehensive recognition is necessary for the understanding of long COVID symptoms and their associated factors among nurses and could promote a long COVID symptom management education program targeted at nurses. Moreover, it could facilitate effective nursing care and education plans for long COVID patients.

• Steel and Composite Structures
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• v.50 no.2
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• pp.201-216
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• 2024

This paper is motivated by the lack of studies relating to vibration and nonlinear resonance of fluid-conveying cantilever porous GPLR pipes with fractional viscoelastic model resting on nonlinear foundations. A dynamical model of cantilever porous Graphene Platelet Reinforced (GPLR) pipes conveying fluid and resting on nonlinear foundation is proposed, and the vibration, natural frequencies and primary resonant of such system are explored. The pipe body is considered to be composed of GPLR viscoelastic polymeric pipe with porosity in which Halpin-Tsai scheme in conjunction with fractional viscoelastic model is used to govern the construction relation of the nanocomposite pipe. Three different porosity distributions through the pipe thickness are introduced. The harmonic concentrated force is also applied on pipe and excitation frequency is close to the first natural frequency. The governing equation for transverse motion of the pipe is derived by the Hamilton principle and then discretized by the Galerkin procedure. In order to obtain the frequency-response equation, the differential equation is solved with the assumption of small displacement, damping coefficient, and excitation amplitude by the multiple scale method. A parametric sensitivity analysis is carried out to reveal the influence of different parameters, such as nanocomposite pipe properties, fluid velocity and nonlinear viscoelastic foundation coefficients, on the primary resonance and linear natural frequency. Results indicate that the GPLs weight fraction porosity coefficient, fractional derivative order and the retardation time have substantial influences on the dynamic response of the system.

• Advances in nano research
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• v.16 no.3
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• pp.231-249
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• 2024

When the amplitude of the vibrations is equivalent to that clearance, the vibrations for small amplitudes will really be significantly nonlinear. Nonlinearities will not be significant for amplitudes that are rather modest. Finally, nonlinearities will become crucial once again for big amplitudes. Therefore, the concrete panel system may experience a big amplitude in this work as a result of the high temperature. Based on the 3D modeling of the shell theory, the current work shows the influences of the von Kármán strain-displacement kinematic nonlinearity on the constitutive laws of the structure. The system's governing Equations in the nonlinear form are solved using Kronecker and Hadamard products, the discretization of Equations on the space domain, and Duffing-type Equations. Thermo-elasticity Equations. are used to represent the system's temperature. The harmonic solution technique for the displacement domain and the multiple-scale approach for the time domain are both covered in the section on solution procedures for solving nonlinear Equations. An effective data-driven solution is often utilized to predict how different systems would behave. The number of hidden layers and the learning rate are two hyperparameters for the network that are often chosen manually when required. Additionally, the data-driven method is offered for addressing the nonlinear vibration issue in order to reduce the computing cost of the current study. The conclusions of the present study may be validated by contrasting them with those of data-driven solutions and other published articles. The findings show that certain physical and geometrical characteristics have a significant effect on the existing concrete panel structure's susceptibility to temperature change and GPL weight fraction. For building construction industries, several useful recommendations for improving the thermo-mechanics' behavior of structural concrete panels are presented.