• Women's Health Nursing
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• v.27 no.1
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• pp.14-26
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• 2021

Purpose: This study aimed to identify the effects of nursing intervention programs for women with gestational diabetes mellitus (GDM) through a critical review of recent studies. Methods: Studies related to effects of nursing intervention programs for women with GDM published in English or Korean between 2000 and 2019 were extracted from 10 electronic databases. The quality of the studies was evaluated and double-checked for accuracy by two reviewers using the Revised Cochrane Risk-of-Bias tool for randomized controlled trials. Results: Twenty studies were selected, of which 19 had a low risk of bias and one had a high risk of bias. Interventions fell into six main groups: (1) integrated interventions, (2) self-monitoring of blood glucose levels, (3) dietary interventions, (4) exercise, (5) psychotherapy, and (6) complementary therapy. This review found that nursing interventions for GDM were of many types, and integrated interventions were the most common. However, low-carbohydrate diets and blood glucose monitoring interventions did not show statistically significant results. Evidence shows that various nursing intervention programs applied to GDM improved diverse aspects of maternal, fetal, and neonatal health, including both physical and psychological aspects. Conclusion: The composition and delivery of integrated interventions continue to evolve, and these interventions affect physical and psychological indicators. Although interventions affecting physical health indicators (e.g., blood glucose levels, diet, and exercise) are important, many studies have shown that programs including psycho-emotional nursing interventions related to anxiety, depression, stress, self- efficacy, and self-management are also highly useful.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.51-60
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• 2021

Effective nonpoint source (NPS) pollution management requires frequent water quality monitoring, which is, however, often costly to be implemented in practice. Statistical techniques and machine learning methods allow us to identify and focus on fundamental environmental variables that have close relationships with NPS pollutants of interest. This study developed surrogate models to predict the concentrations of suspended sediment (SS) and total phosphorus (T-P) from turbidity and runoff discharge rates using multiple linear regression (MLR) and random forest (RF) methods. The RF models provided acceptable performance in predicting SS and T-P, especially when runoff discharge rates were high. The RF models outperformed the MLR models in all the cases. Such finding highlights the potential of RF techniques and models as a tool to identify fundamental environmental variables that are measured in relatively inexpensive ways or freely available but still able to provide information required to quantify the concentrations of NP S pollutants. The analysis of relative importance rates showed that the temporal variations of SS and T-P concentrations could be more effectively explained by that of turbidity than runoff discharge rate. This study demonstrated that the advanced statistical techniques such as machine learning could help to improve the efficiency of NPS pollutants monitoring.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.27-37
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• 2020

The Fukushima Daiichi accident in 2011 revealed some vulnerabilities of existing Nuclear Power Plants (NPPs) under extended Station Blackout (SBO) accident conditions. One of the key Severe Accident Management (SAM) strategies developed post Fukushima accident is the In-Vessel Retention (IVR) Strategy which aims to retain the structural integrity of the Reactor Pressure Vessel (RPV). RELAP/SCDAPSIM/MOD3.4 is selected to predict the thermal-hydraulic response of APR1400 undergoing an extended SBO. To assess the effectiveness of the IVR strategy, it is essential to quantify the underlying uncertainties. In this work, both the epistemic and aleatory uncertainties are considered to identify the success window of the IVR strategy. A set of in-vessel relevant phenomena were identified based on Phenomena Identification and Ranking Tables (PIRT) developed for severe accidents and propagated through the thermal-hydraulic model using Wilk's sampling method. For this work, a Systems Engineering (SE) approach is applied to facilitate the development process of assessing the reliability and robustness of the APR1400 IVR strategy. Specifically, the Kossiakoff SE method is used to identify the requirements, functions and physical architecture, and to develop a design verification and validation plan. Using the SE approach provides a systematic tool to successfully achieve the research goal by linking each requirement to a verification or validation test with predefined success criteria at each stage of the model development. The developed model identified the conditions necessary for successful implementation of the IVR strategy which maintains the vessel integrity and prevents a melt-through.

• Journal of radiological science and technology
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• v.44 no.6
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• pp.599-605
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• 2021

The International Electrotechnical Commission (IEC) 62494-1 has defined the exposure index (EI) that have a proportional relationship with the dose incident on the image receptor, and target exposure index (EI_T), deviation index (DI). In this study, an appropriate EI_T for skull radiography was established through the diagnostic reference level (DRL) and changes in DI were confirmed. Entrance surface dose (ESD) and EI were obtained using the computed radiography system displayed the EI as per IEC on console and skull phantom by experiment based on the national average exposure conditions announced in 2012 and 2019. And appropriate EI_T was established by applying the DRL in 2012 and 2019. As a results, the EI_T is changed according to the change in the DRL, and the exposure condition that becomes the ideal DI according to the change in the EI_T also has a difference of about 1.41 times. DRL is recommended to optimize the patient dose, however it is difficult to measure in real time at medical institutions whereas EI and DI are displayed on the console at the same time as exposure. When the EI_T is set based on the DRL and the DI is closed to an ideal value, it is useful as a patient dose management tool. Therefore, when the EI_T is periodically managed along with the revision of the DRLs, the patient dose can be optimized through the EI, EI_T and DI.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.309-319
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• 2022

In previous studies, stress in the Information and Communication Technology (ICT) work environment was focused on lowering work performance by negatively affecting the emotions of organizational members. In the current corona pandemic era, as the ratio of organizational members working from home in a smart environment increases, the need for research on the effects of positive and negative stress on work performance is being raised. Accordingly, by applying the Affective Event Theory to the emotional effects of stress on employees' emotional responses, the effects on work performance were analyzed by dividing them into positive and negative emotions. Also, the effect of smart work on work performance was analyzed. This survey was commissioned by a research company and analyzed using Smart PLS 3.0 tool. Therefore, based on the research results, it was suggested that stress does not only negatively affect the emotions of employees, but that the challenge stress that appears in the mind to achieve a goal induces positive emotions in the employees' emotions and helps to improve work performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.161-166
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• 2022

In this paper, we analyze the problems that occur when performing the big data analysis using R as a data analysis tool, and present the usefulness of the data analysis with SparkR which connects R and Spark to support distributed processing of big data effectively. First, we study the memory allocation problem of R which occurs when loading large amounts of data and performing operations, and the characteristics and programming environment of SparkR. And then, we perform the comparison analysis of the execution performance when linear regression analysis is performed in each environment. As a result of the analysis, it was shown that R can be used for data analysis through SparkR without additional language learning, and the code written in R can be effectively processed distributedly according to the increase in the number of nodes in the cluster.

• Imaging Science in Dentistry
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• v.52 no.2
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• pp.209-217
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• 2022

Purpose: The aim of this study was, firstly, to determine the concordance of ultrasonographic and histopathological diagnoses in patients in whom apical resection was already indicated. Secondly, this study aimed to determine whether lesions were periapical granulomas or cysts, and to compare them after root canal treatment using ultrasonography and periapical radiographs. Materials and Methods: In the first stage of the study, ultrasonographic and histopathologic diagnoses of 10 lesions were compared. Secondly, the periapical radiographs and ultrasonographic images of 44 lesions were measured. The presence of internal vascularity was determined by ultrasonographic color and power Doppler modes. Follow-up examinations of healing after root canal treatment were performed using ultrasonography and periapical radiographs, and these modalities were compared. Results: In the periapical granuloma and cyst groups, the measurement values decreased for all variables. There was no significant difference in the dimensional changes of lesions between the 2 groups, and ultrasonography and periapical radiographs were compatible. The pre-diagnoses were compared with histopathological diagnoses and were found to be compatible. Conclusion: The ultrasonographic color and power Doppler techniques could be an effective method for diagnosing periapical lesions as cysts or granulomas. After root canal treatment of granulomas and cysts, the dimensional shrinkage and healing patterns appear to be similar. Ultrasonography and periapical radiographs were consistent in terms of dimensional comparisons, and ultrasonography may be an alternative method for follow-up of the healing of periapical lesions.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.102-114
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• 2021

Biofouling represents an important problem in the shipping industry since it causes the increase in surface roughness. The most of ships in the current world fleet do not have good coating condition which represents an important problem due to strict rules regarding ship energy efficiency. Therefore, the importance of the control and management of the hull and propeller fouling is highlighted by the International Maritime Organization and the maintenance schedule optimization became valuable energy saving measure. For adequate implementation of this measure, the accurate prediction of the effects of biofouling on the hydrodynamic characteristics is required. Although computational fluid dynamics approach, based on the modified wall function approach, has imposed itself as one of the most promising tools for this prediction, it requires significant computational time. However, during the maintenance schedule optimization, it is important to rapidly predict the effect of biofouling on the ship hydrodynamic performance. In this paper, the effect of biofilm on the ship hydrodynamic performance is studied using the proposed performance prediction method for three merchant ships. The applicability of this method in the assessment of the effect of biofilm on the ship hydrodynamic performance is demonstrated by comparison of the obtained results using the proposed performance prediction method and computational fluid dynamics approach. The comparison has shown that the highest relative deviation is lower than 4.2% for all propulsion characteristics, lower than 1.5% for propeller rotation rate and lower than 5.2% for delivered power. Thus, a practical tool for the estimation of the effect of biofouling with lower fouling severity on the ship hydrodynamic performance is developed.

• Journal of KIBIM
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• v.11 no.4
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• pp.31-41
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• 2021

Digital twins between "BIM Digital Model-Physical Prototype Model" will be built for Noise Barrier tunnel(NBT) that meet the definition of N.G smart city facilities derived from previous studies to build a data flow that connects data at each stage of design, construction, and operation. In this process, BIM design automation tools are created and utilized, and consistent transmission of member and attribute data is performed by converting them into IFC format. Through this, the purpose is to improve the labor-intensive environment required from the design stage of the NBT and to consistently maintain the information required for subsequent production and construction. This includes achieving changes in the construction industry based on digital transformation by unifying various data formats used differently for each industry from design to operation. In addition, it demonstrates that information exchange in the maintenance and management stages is possible based on the data exchange of the established digital twin and aims to improve the existing labor-intensive environment and expand operability between digital and physical information. As suggested in previous studies, the implementation of digital twins in these N.G smart city facilities includes the possibility of building an environment that adds to the possibility of high value-added product platforms as well as the function of big data platforms targeting existing smart cities.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.255-263
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• 2021

Background: Ecosystem service mapping is an important tool for decision-making in landscape planning and natural resource management. Today, pollination service mapping is based on the Lonsdorf model (InVEST software) that determines the availability of nesting and floral resources for each land cover and estimates pollination according to the foraging range of the desired species. However, it is argued that the Lonsdorf model has significant limitations in estimating pollination in a landscape that can affect the results of this model. Results: This paper presents a free software, named PollMap, that does not have the limitations of the Lonsdorf model. PollMap estimates the pollination service according to a modified version of the Lonsdorf model and assumes that only cells within the flight range of bees are important in the pollination mapping. This software is produced for estimating and mapping crop pollination in agricultural landscapes. The main assumption of this software is that in the agricultural landscapes, which are dominated by forest and agriculture ecosystems, forest patches serve only as a nesting habitat for wild bees and the surrounding fields provide floral resources. Conclusion: The present study provided new software for mapping crop pollination in agricultural landscapes that does not have the limitations of the Lonsdorf model. We showed that the use of the Lonsdorf model for pollination mapping requires attention to the limitations of this model, and by removing these limitations, we will need new software to obtain a reliable mapping of pollination in agricultural landscapes.