• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.201-212
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• 2022

Prior to the emergence of Covid-19, Saudi Arabia (SA) had never faced the challenge of dealing with a global pandemic. Significantly, the current crisis has impacted all industries and sectors in the country, including the healthcare system, and has led to an emphasis on human life being more precious and valuable than economic profit. This study focuses on the impact of Covid-19 on the health of nurses, including their quality of life, during 2020. Understanding the position of the nursing profession during the pandemic, including the most effective methods of preventing work-related stress is important. Information was acquired through an online survey method (i.e. self-completion), known as the Expanded Nursing Stress Scale (ENSS), which was distributed to nurses in all regions of SA. It was found that the main aspects impacting nurses' work-related stress include gender, employment type, training, and dealing with infected patients. In addition, they highlight that such stress plays a substantial role in patient safety and nurses' satisfaction at work, as well as the future survival of organizations. The emergence of Covid-19 as a novel infectious disease has increased nurses' uncertainty and work-related stress. The results of this research will provide insights into the views of both nurses and their managers, in order to identify the main indicators of stress.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.609-625
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• 2023

This study is a demand research for the selection of public safety science and technology equipment and suggests an empirical research method. The technology demand survey is the beginning of the selection of innovative technology. And it is the basis of collecting information required for the technology required in the market and helping to apply it to the field. The demand survey for police science and technology can reduce the uncertainty of crime prevention and help the smooth implementation of security policies. However, in Korea, adoption of security science and technology equipment was centered on social issues or researchers' opinions rather than the demands of field users. Until, there was no research has been conducted on the demands of field police officers for selection of security science and technology equipment in Korea. Also, there was no preferential study for the demand for security science and technology equipment. Therefore, this study proposes a methodology that can systematically identify the needs for the technology and equipment of field experts suitable for the public security situation for the selection of security science and technology equipment. Specifically, we propose a sample design for a technology classification system and a survey tool for technology awareness and satisfaction. It is expected that this tool will provide a classification system for security science and technology equipment selected for the Korean police and will help determine the priority of equipment suitable for the field.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1528-1539
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• 2023

Since the leakage of sodium in an SFR (sodium-cooled fast reactor) causes an explosion upon reaction with air and water, sodium leakages represent an important safety issue. In this study, a novel technique for improving the reliability of sodium leakage detection applying DDVR (dynamic data validation and reconciliation) is proposed and verified to resolve this technical issue. DDVR is an approach that aims to improve the accuracy of a target system in a dynamic state by minimizing random errors, such as from the uncertainty of instruments and the surrounding environment, and by eliminating gross errors, such as instrument failure, miscalibration, or aging, using the spatial redundancy of measurements in a physical model and the reliability information of the instruments. DDVR also makes it possible to estimate the state of unmeasured points. To validate this approach for supporting sodium leakage detection, this study applies experimental data from a sodium leakage detection experiment performed by the Korea Atomic Energy Research Institute. The validation results show that the reliability of sodium leakage detection is improved by cooperation between DDVR and hardware measurements. Based on these findings, technology integrating software and hardware approaches is suggested to improve the reliability of sodium leakage detection by presenting the expected true state of the system.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.1-6
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• 2023

This paper presents a comprehensive scheme for assessing the importance of multiple microgrids (MGs) network that includes distributed energy resources (DERs), renewable energy systems (RESs), and energy storage system (ESS) facilities. Due to the uncertainty of severe weather, large-scale cascading failures are inevitable in energy networks. making the assessment of the structural vulnerability of the energy network an attractive research theme. This attention has led to the identification of the importance of measuring energy nodes. In multiple MG networks, the energy nodes are regarded as one MG. This paper presents a modified PageRank algorithm to assess the importance of MGs that include multiple DERs and ESS. With the importance rank order list of the multiple MG networks, the core MG (or node) of power production and consumption can be identified. Identifying such an MG is useful in preventing cascading failures by distributing the concentration on the core node, while increasing the effective link connection of the energy flow and energy trade. This scheme can be applied to identify the most profitable MG in the energy trade market so that the deployment operation of the MG connection can be decided to increase the effectiveness of energy usages. By identifying the important MG nodes in the network, it can help improve the resilience and robustness of the power grid system against large-scale cascading failures and other unexpected events. The proposed algorithm can point out which MG node is important in the MGs power grid network and thus, it could prevent the cascading failure by distributing the important MG node's role to other MG nodes.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• Journal of Wellbeing Management and Applied Psychology
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• v.7 no.1
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• pp.1-7
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• 2024

Purpose: The improvement of the social security system can greatly affect residents' future uncertainty, and it is important to study the relationship between public pensions and household consumption. Research design, data and methodology: Using the 2018 China Household Panel Survey (CFPS) data, the instrumental variable method is used to analyze the impact of pension insurance on urban residents' consumption. Results: The results of the study show that there are differences in the impact of three different pension insurance systems on household consumption. The pension insurance for public sector significantly boosts household consumption, and having a pension insurance for public sector can increase household consumption by 7.7%. The pension insurance for enterprise employee will reduce household consumption, but this is only significant for urban households. The pension insurance for urban and rural residents has a negative impact on household consumption. For the 16- to 39-year-old group, having a pension insurance for urban and rural residents will reduce household consumption by 5.7%. At the same time, household income, assets, scale, and education level will positively stimulate household consumption. Conclusions: The study reveals varying impacts among different pension types, highlighting the need for optimizing social security schemes to incentivize higher consumption rates.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.83-92
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• 2024

It is a common observation that whenever any patient arrives at the front desk of a hospital, outpatient clinic, or other health-associated centers, they have to first queue up in a line and wait to fill in their registration form to get admitted. The long waiting time without any status updates is the most common complaint, worrying health officials. In this paper, UrNext, a location-aware mobile-based solution using Bluetooth low-energy (BLE) technology, is presented to solve the problem. Recently, a technology-oriented method has been gaining popularity in solving the healthcare sector's problems, namely the Internet of Things (IoT). The implementation of this solution could be explained through a simple example that when a patient arrives at a clinic for her consultation. There, instead of having to wait in long lines, she will be greeted automatically, receive a push notification telling her that she has been admitted along with an estimated waiting time for her consultation session. This will not only provide the patients with a sense of freedom but would also reduce uncertainty levels that are generally observed, thus saving both time and money. This work aimed to improve clinics' quality of services and organize queues and minimize waiting times in clinics, leading to patient comfortability and reducing the burden on nurses and receptionists. The results demonstrated that the presented system was successful in its performance and helped achieve high usability.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.364-374
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• 2024

Today, risks created by uncertainty must be managed for successful project execution. From this perspective, applying a risk management process is very important for successful defense systems test works. This paper describes 'the implentation of risk management process for test work' carried out by DTERI's process improvement activities. In this study, the concept of risk management process, and details of the risk management process are examined through PMBOK and ISO/IEC/IEEE 15288, CMMI. After that, we defined 'Standard Process for Risk Management' of defence systems test works. And, we describe 'Risk Management Function' of DTERI's Project Management System(PMS) and the risk management process of DTERI. Finally, the effectiveness of the risk management standard process is verified through quantitative analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.93-106
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• 2024

As the complexity and uncertainty of international construction projects increase, the importance of risk management capabilities in the construction industry has become more pronounced. Accordingly, Enterprise Risk Management (ERM) has become a widely adopted approach among organizations as a new way for more effective risk management. Despite its growing application, research related to ERM is still in its infancy, and most of the existing studies have been limited to financial industries. Therefore, this study aims to empirically examine the influence of ERM's core elements on project risk management (PRM) and project performance within construction firms. Our findings indicate that the key ERM components-organization, policy, and culture-significantly enhance PRM processes, underscoring their critical role and importance. Additionally, effective PRM positively affects project outcomes, highlighting its significance for construction companies engaged in international projects. While ERM does not directly impact project performance, it indirectly improves outcomes through enhanced PRM capabilities. It suggests that ERM will contribute to the firm's performance by improving the firm's PRM capability through policies and a risk-focused culture corresponding to the adopted ERM organization and system..

• Journal of Korea Water Resources Association
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• v.41 no.11
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• pp.1079-1094
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• 2008

This study is to evaluate the impact of varying spatial resolutions on the uncertainty of Soil and Water Assessment Tool (SWAT) predicted streamflow, non-point source (NPS) pollution loads transport in a small agricultural watershed (1.21 $km^2$) for three cases of model input; Case A is the combination of 2 m DEM, QuickBird land use, Case B is the combination of 10 m DEM, 1/25,000 land use, and Case C is the combination of 30 m DEM, Landsat land use, soil data is used 1/25,000 for three cases respectively. The model was calibrated for 2 years (1999-2000) using daily streamflow and monthly water quality records, and verified for another 2 years (2001-2002). The average Nash and Sutcliffe model efficiency was 0.59 for streamflow and RMSE were 2.08, 4.30 and 0.70 tons/yr for sediment, T-N and T-P respectively. The model was run for a small agricultural watershed with three cases of spatial input data. The hydrological results showed that output uncertainty was biggest by spatial resolution of land use. Streamflow increase the watershed average CN value of QucikBird land use was 0.4 and 1.8 higher than those of 1/25,000 and Landsat land use caused increase of streamflow. On the other hand, The NPS loadings from the model prediction showed that the sediment, T-N and T-P of QuickBird land use (Case A) showed 23.7 %, 43.3 % and 48.4 % higher value than 1/25,000 land use (Case B) and 50.6 %, 50.8 % and 56.9 % higher value than Landsat land use (Case C) respectively.