• Korean Journal of Occupational Health Nursing
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• v.31 no.4
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• pp.167-177
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• 2022

Purpose: This cross-sectional study aimed to evaluate the mediating and moderating effects of resilience in the relationship between experience of workplace bullying and its consequences among hospital nurses. Methods: The participants included 187 registered nurses working in general hospitals or a tertiary hospital in Busan and Gyeongnam Province, South Korea. Data were collected from October 25-November 30, 2019, using structured questionnaires. The moderating effects were examined using stepwise hierarchical multiple regression models. Data were analyzed using the SPSS/WIN 23.0 statistical program. Results: The results demonstrated that resilience had a moderating role in the relationship between experience of workplace bullying and its consequences in hospital nurses (β=.01, p=.024). However, resilience showed no mediating effect. Conclusion: To prevent and control workplace bullying, as well as to minimize its negative effects, it is necessary to develop a program that can enhance the resilience of hospital nurses.

• Journal of Microbiology and Biotechnology
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• v.32 no.12
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• pp.1515-1526
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• 2022

Eukaryotic chromatin is highly organized in the 3D nuclear space and dynamically regulated in response to environmental stimuli. This genomic organization is arranged in a hierarchical fashion to support various cellular functions, including transcriptional regulation of gene expression. Like other host cellular mechanisms, viral pathogens utilize and modulate host chromatin architecture and its regulatory machinery to control features of their life cycle, such as lytic versus latent status. Combined with previous research focusing on individual loci, recent global genomic studies employing conformational assays coupled with high-throughput sequencing technology have informed models for host and, in some cases, viral 3D chromosomal structure re-organization during infection and the contribution of these alterations to virus-mediated diseases. Here, we review recent discoveries and progress in host and viral chromatin structural dynamics during infection, focusing on a subset of DNA (human herpesviruses and HPV) as well as RNA (HIV, influenza virus and SARS-CoV-2) viruses. An understanding of how host and viral genomic structure affect gene expression in both contexts and ultimately viral pathogenesis can facilitate the development of novel therapeutic strategies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2101-2123
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• 2023

Recent studies have shown that the neural network-based binary code similarity detection technology performs well in vulnerability mining, plagiarism detection, and malicious code analysis. However, existing cross-architecture methods still suffer from insufficient feature characterization and low discrimination accuracy. To address these issues, this paper proposes a cross-architecture binary function similarity detection method based on composite feature model (SDCFM). Firstly, the binary function is converted into vector representation according to the proposed composite feature model, which is composed of instruction statistical features, control flow graph structural features, and application program interface calling behavioral features. Then, the composite features are embedded by the proposed hierarchical embedding network based on a graph neural network. In which, the block-level features and the function-level features are processed separately and finally fused into the embedding. In addition, to make the trained model more accurate and stable, our method utilizes the embeddings of predecessor nodes to modify the node embedding in the iterative updating process of the graph neural network. To assess the effectiveness of composite feature model, we contrast SDCFM with the state of art method on benchmark datasets. The experimental results show that SDCFM has good performance both on the area under the curve in the binary function similarity detection task and the vulnerable candidate function ranking in vulnerability search task.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.2
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• pp.161-169
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• 2023

Purpose: This study was conducted to identify the effects of grit on the work engagement of nurses and to identify the mediating effects of positive psychological capital and burnout in the relationship between grit and work engagement. Methods: The study subjects were 182 nurses who had been working in a general hospital for more than six months. The data were collected from July 12 to July 26, 2021. The collected 182 sets of data were analyzed by descriptive statistics, correlation analysis, and a hierarchical regression analysis using IBM SPSS statistics version 23.0 and also by bootstrapping using SPSS Process Macro. Results: As a result of the analyses, it was found that higher work engagement was associated with higher grit, higher positive psychological capital, and lower burnout. The mediating effects of positive psychological capital and burnout in the relationship between grit and work engagement were found to be both direct and indirect. Conclusion: This study provides basic data suggesting that an education program designed to reduce burnout and reinforce grit and positive psychological capital is necessary to promote the work engagement of nurses in clinical settings.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.559-563
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• 2015

Identification of energy use patterns in buildings has a great opportunity for energy saving. To find what energy use patterns exist, clustering analysis has been commonly used such as K-means and hierarchical clustering method. In case of high dimensional data such as energy use time-series, data reduction should be considered to avoid the curse of dimensionality. Principle Component Analysis, Autocorrelation Function, Discrete Fourier Transform and Discrete Wavelet Transform have been widely used to map the original data into the lower dimensional spaces. However, there still remains an ongoing issue since the performance of clustering analysis is dependent on data type, purpose and application. Therefore, we need to understand which data reduction techniques are suitable for energy use management. This research aims find the best clustering method using energy use data obtained from Seoul National University campus. The results of this research show that most experiments with data reduction techniques have a better performance. Also, the results obtained helps facility managers optimally control energy systems such as HVAC to reduce energy use in buildings.

• Korea Trade Review
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• v.47 no.3
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• pp.17-35
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• 2022

The Pandemic crisis caused by COVID-19 has raised awareness of the importance of supply chain risk management, such as the control of movement between countries and the simultaneous manufacturing paralysis in the world. Effective risk management within the supply chain of the company is a core competency in the global environment. Therefore, this study quantitatively analyzed the perspective of domestic large corporations and small and medium enterprises (SMEs) by using the hierarchical analysis method (AHP) to identify the factors that should be considered as the priority when establishing supply chain risk management plans for large and small business employees. In order to conduct the study, a survey was conducted on large corporations and small and medium enterprises in Gyeongnam and Busan, and AHP analysis was conducted using Microsoft 365 excel program. In addition, Mann-Whitney U test (independent sample-nonparametric test) was conducted using SPSS/18 version of statistical package program for comparative analysis between groups. As a result, the priority was highly evaluated in the order of financial ability, competitiveness, disaster in the overall priority evaluation. There were statistically significant differences in internal risk and strategic decision making of supply chain between groups. This suggests that fandemics such as COVID-19 can not be predicted, but strategic responses are needed to utilize opportunities expressed in the crisis through supply chain risk management and to increase the competitive advantage of domestic companies even in the crisis.

• Corrosion Science and Technology
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• v.22 no.5
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• pp.377-386
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• 2023

Aircraft washing is performed periodically for corrosion control. Currently, the aircraft washing interval is qualitatively set according to the geographical conditions of each base. We developed a washing interval determination algorithm based on atmospheric corrosion environment monitoring data at the Republic of Korea Air Force (ROKAF) bases and United States Air Force (USAF) bases to determine the optimal interval. The main factors of the washing interval decision algorithm were identified through hierarchical clustering, sensitivity analysis, and analysis of variance, and criteria were derived. To improve the classification accuracy, we developed a washing interval decision model based on an artificial neural network (ANN). The ANN model was calibrated and validated using the atmospheric corrosion environment monitoring data and washing intervals of the USAF bases. The new algorithm returned a three-level washing interval, depending on the corrosion rate of steel and the results of the ANN model. A new base-specific aircraft washing interval was proposed by inputting the atmospheric corrosion environment monitoring results of the ROKAF bases into the algorithm.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.645-652
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• 2023

The aleurone layer in maize is crucial as it contains essential nutrients such as minerals, vitamins, and high-quality proteins. While most of the maize varieties are known to possess a single aleurone layer, several multi-aleurone layer mutants and landraces have been suggested for hierarchical genetic control of aleurone development. Conventional microscopy analysis often involves using immature seeds or sampling only a portion of the kernel sample, and whole kernel section analysis using a microtome is technically difficult and time-consuming. Additionally, the larger size of maize kernels posed challenges for comprehensive cross-sectional analysis compared to other cereal crops. Consequently, this study aimed to develop an efficient method to comprehensively understand the aleurone layer characteristics of the entire cross-section in maize. Through observations of diverse maize genetic resources, we confirmed irregular aleurone layer patterns in those with multiple aleurone layers, and we discovered a landrace having multiple aleurone layers. By selectively identifying genetic resources with multiple aleurone layers, this method may contribute to efficient breeding processes in maize.

• The Korean Journal of Emergency Medical Services
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• v.28 no.1
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• pp.21-34
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• 2024

Purpose: This study aimed to observe change in factors over time in the first cohort of the 2018 Children and Adolescent Panel Middle School. In addition, this study attempted to examine the causal relationship and influence between variables by setting a time gap between independent and dependent variables. Methods: Frequency and descriptive statistical analyses were conducted to determine the general characteristics of the study participants. Hierarchical regression analysis was conducted to analyze the effects of smartphone dependence on health, sleep quality, and depression. After inputting the control variables (Model 2), the influence of the variables was identified based on the input model. Results: Smartphone dependence positively impacted depression in both male and female students and negatively impacted sleep and health. Conclusion: Smartphones are closely associated with teenagers' lives. Additionally, as adolescents experience various psychological anxieties owing to rapid physical changes, there are concerns that psychological dependence may increase, considering that adolescence is the most emotionally unstable period. Therefore, the results of this study consistently prove that smartphone dependence has a causal relationship with emotion-related variables, such as emotional stress, depression, and anxiety.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.144-150
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• 2024

There is no prior research on organizational commitment and supervision for social welfare public officials in charge of public-private cooperation in public welfare fields. Therefore we are designed to determine the impact of social welfare public officials' public-private cooperation awareness on organizational commitment to verify the moderating effect of supervision on the effect between public-private cooperation awareness and organizational commitment. The analysis data is 242 questionnaires collected from Incheon public health and welfare officials visiting towns, villages, and villages in 10 counties. Using the SPSS 22.0 program, descriptive statistics and relationships between variables were analyzed, regression analysis was performed to analyze the influence between variables, and hierarchical regression analysis was performed to verify supervision control. As a result of the study, it was confirmed that the perception of public-private cooperation affects organizational commitment, interacts with supervision satisfaction, and has a moderating effect. Based on this, in order to improve the organizational commitment of social welfare public officials during public-private cooperation work, specific measures were proposed for sharing awareness and understanding between the public and private sectors, establishing an official system, and establishing a supervision system.