• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.46-58
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• 2023

Deterministic safety analysis is a crucial part of safety assessment, particularly when it comes to demonstrating the safety of nuclear power plant designs. The traditional approach to deterministic safety analysis models is to model the nuclear core using point kinetics. However, this simplified approach does not fully reflect the real core behavior with proper moderator and fuel reactivity feedbacks during the transient. The use of Multi-Physics approach allows more precise simulation reflecting the inherent three-dimensionality (3D) of the problem by representing the detailed 3D core, with instantaneous updates of feedback mechanisms due to changes of important reactivity parameters like fuel temperature coefficient (FTC) and moderator temperature coefficient (MTC). This paper addresses a CEA ejection accident at hot full power (HFP), in which the underlying strong and un-symmetric feedback between thermal-hydraulics and reactor kinetics exist. For this purpose, a multi-physics analysis tool has been selected with the nodal kinetics code, 3DKIN, implicitly coupled to the thermal-hydraulic code, RELAP5, for real-time communication and data exchange. This coupled approach enables high fidelity three-dimensional simulation and is therefore especially relevant to reactivity initiated accident (RIA) scenarios and power distribution anomalies with strong feedback mechanisms and/or un-symmetrical characteristics as in the CEA ejection accident. The Systems Engineering approach is employed to provide guidance in developing the work in a systematic and efficient fashion.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2381-2398
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• 2024

The construction of virtual indoor spaces is crucial for the development of metaverses, virtual production, and other 3D content domains. Traditional methods for creating these spaces are often cost-prohibitive and labor-intensive. To address these challenges, we present a pipeline for generating digital twins of real indoor environments from RGB-D camera-scanned data. Our pipeline synergizes space structure estimation, 3D object detection, and the inpainting of missing areas, utilizing deep learning technologies to automate the creation process. Specifically, we apply deep learning models for object recognition and area inpainting, significantly enhancing the accuracy and efficiency of virtual space construction. Our approach minimizes manual labor and reduces costs, paving the way for the creation of metaverse spaces that closely mimic real-world environments. Experimental results demonstrate the effectiveness of our deep learning applications in overcoming traditional obstacles in digital twin creation, offering high-fidelity digital replicas of indoor spaces. This advancement opens for immersive and realistic virtual content creation, showcasing the potential of deep learning in the field of virtual space construction.

• Archives of Plastic Surgery
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• v.51 no.3
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• pp.268-274
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• 2024

Most Asians have a nose with a short columella and a low dorsum; augmentation rhinoplasty using implants is commonly performed in Asian countries to achieve a taller and more well-defined nasal dorsum. However, the current knowledge is insufficient to fully understand the various subjective desires of patients, reflect on them during surgery, or to objectively analyze the results after surgery. Advances in digital imaging technologies, such as 3D printing and 3D scanning, have transformed the medical system from hospital-centric to patient-centric throughout the medical field. In this study, we applied these techniques to rhinoplasty. First, we used virtual 3D plastic surgery software to enable surgical planning through objectified numerical calculations based on the visualized data of the patient's medical images rather than simple virtual plastic surgery. Second, the customized nasal implant was manufactured by reflecting the patient's anatomical shape and virtual 3D plastic surgery data. Taken together, we describe the surgical results of applying these rhinoplasty solutions in four patients. Our experience indicates that high fidelity and patient satisfaction can be achieved by applying these techniques.

• Nuclear Engineering and Technology
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• v.56 no.10
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• pp.4195-4206
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• 2024

Compared to traditional transverse integration methods, the variational nodal method, with its unique advantages, is more suitable for high-fidelity calculations of reactor physics in reactors with complex geometries and finer detail descriptions. In this study, the basic theory of the variational nodal method was derived and the VINUS code is developed. The neutron solver based on this method is adaptable to various geometric models, and showcased the code's fundamental framework. On this basis, a set of self-designed macroscopic cross-section benchmarks, actual macroscopic cross-section benchmark VVER-440, and few-group microscopic cross-section benchmark RBEC-M for fast spectrum reactors were used to verify different functionalities of VINUS. The results were shown that VINUS code maintains good computational accuracy and convergence trends. For the VVER-440 benchmarks, the deviation of k_eff of VINUS from reference is less than 100 pcm, and the maximum power deviation is less than 4 %. For the RBEC-M, the deviation of k_eff is 125 pcm, and the maximum power deviation is less than 5 %. These outcomes collectively demonstrate the solver's potential for engineering applications in future advanced reactor designs.

• The Journal of Korean Academy of Prosthodontics
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• v.40 no.6
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• pp.545-559
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• 2002

There has been increasing use of IPS Empress $2^{(R)}$ owing to easy fabrication method, high esthetics similar to natural teeth, good marginal accuracy, and sufficient fracture strength. However, in clinical application, although a luting agent and the tooth cementation bonding procedure influence the marginal accuracy and fracture strength restoration, there has been a controversy in the selection of proper luting agent. This study was to measure the marginal fidelites and fracture strength of IPS Empress crowns according to three cement types, Protec $cem^{(R)}$, Variolink $II^{(R)}$ and Panavia $21^{(R)}$. After construction of 12 experimental dies for each group, IPS Empress $2^{(R)}$ crowns were fabricated and luted the metal master die prepartion of the maxillary right premolar. Marginal gaps before cementation and after cementation were measured. Buccal incline on the functional cusp of specimens were loaded until the catastrophic failure and fracture strength was measured. The results of this study were as follows: 1. The range of gap was $34.04{\pm}4.84{\mu}m$ before cementation and $37.88{\pm}5.00{\mu}m$ after cementation, which showed significant difference by paired t-test (p<0.05). The difference in the results from marginal accuracy according to measuring point proved to be not statistically significant by two-way ANOVA test (p>0.05). 2. The difference in the results from marginal accuracy according to three cement types Proved that The Variolink $II^{(R)}$ cement group had the least gap, $35.43{\pm}5.03{\mu}m$, and showed superior marginal accuracy while there existed statistic significance in Protec $cem^{(R)}$ cement group, $39.06{\pm}4.41{\mu}m$ or Panavia $21^{(R)}$ cement group, $39.16{\pm}4.39{\mu}m$ by two-way ANOVA test & multiple range test (p<0.05). 3. The difference in the results from fractures strength testing according to three cement type groups proved to be statistically significant (p<0.05). The Variolink $II^{(R)}$ cement group shows highest fracture strength of $1257.33{\pm}226.77N$, Panavia $21^{(R)}$ cement group has $1098.08{\pm}138.45N$, and Protec $cem^{(R)}$ cement group represents the lowest fracture strength of $926.75{\pm}115.75N$. 4. Three different cement groups of different components showed acceptable marginal fidelity and fracture strength. It is concluded that IPS Empress $2^{(R)}$ crowns luted using Variolink $II^{(R)}$ cement group had stronger fracture strength and smaller marginal gap than the other cement groups. Although Variolink $II^{(R)}$ resin cement seemed acceptable to clinical applications in IPS Empress $2^{(R)}$ system, the IPS Empress $2^{(R)}$ system still requires long-term research due to the lack of data in clinical applications.

• Structural Engineering and Mechanics
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• v.37 no.4
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• pp.385-399
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• 2011

The aim of this research is to model the behaviour of recently developed high force to volume (HF2V) passive energy dissipation devices using a simple finite element (FE) model. Thus, the end result will be suitable for use in a standard FE code to enable computationally fast and efficient analysis and design. Two models are developed. First, a detailed axial model that models an experimental setup is created to validate the approach versus experimental results. Second, a computationally and geometrically simpler equivalent rotational hinge element model is presented. Both models are created in ABAQUS, a standard nonlinear FE code. The elastic, plastic and damping properties of the elements used to model the HF2V devices are based on results from a series of quasi-static force-displacement loops and velocity based tests of these HF2V devices. Comparison of the FE model results with the experimental results from a half scale steel beam-column sub-assembly are within 10% error. The rotational model matches the output of the more complex and computationally expensive axial element model. The simpler model will allow computationally efficient non-linear analysis of large structures with many degrees of freedom, while the more complex and physically accurate axial model will allow detailed analysis of joint connection architecture. Their high correlation to experimental results helps better guarantee the fidelity of the results of such investigations.

• Journal of East-West Nursing Research
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• v.26 no.2
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• pp.118-129
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• 2020

Purpose: The purpose of this study was to analyze the topic trend of domestic simulation nursing education research using text network analysis(TNA). Methods: This study was conducted in four steps. TNA was performed using the NetMiner (version 4.4.1) program. Firstly, 245 articles from 4 databases (RISS, KCI, KISS, DBpia) published from 2008 to 2018, were collected. Secondly, keyword-forms were unified and representative words were selected. Thirdly, co-occurrence matrices of keywords with a frequency of 2 or higher were generated. Finally, social network-related measures-indices of degree centrality and betweenness centrality-were obtained. The topic trend over time was visualized as a sociogram and presented. Results: 178 author keywords were extracted. Keywords with high degree centrality were "Nursing student", "Clinical competency", "Knowledge", "Critical thinking", "Communication", and "Problem-solving ability." Keywords with high betweenness centrality were "CPR", "Knowledge", "Attitude", "Self-efficacy", "Performance ability", and "Nurse." Over time, the topic trends on simulation nursing education have diversified. For example, topics such as "Neonatal nursing", "Obstetric nursing", "Pediatric nursing", "Blood transfusion", "Community visit nursing", and "Core basic nursing skill" appeared. The core-topics that emerged only recently (2017-2018) were "High-fidelity", "Heart arrest", "Clinical judgment", "Reflection", "Core basic nursing skill." Conclusion: Although simulation nursing education research has been increasing, it is necessary to continue studies on integrated simulation learning designs based on various nursing settings. Additionally, in simulation nursing education, research is required not only on learner-centered educational outcomes, but also factors that influence educational outcomes from the perspective of the instructors.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.21-29
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• 2019

This paper proposes a novel framework for image fusion of satellite imagery to enhance spatial resolution of the image via structure-texture decomposition. The resolution of the satellite imagery depends on the sensors, for example, panchromatic images have high spatial resolution but only a single gray band whereas multi-spectral images have low spatial resolution but multiple bands. To enhance the spatial resolution of low-resolution images, such as multi-spectral or infrared images, the proposed framework combines the structures from the low-resolution image and the textures from the high-resolution image. To improve the spatial quality of structural edges, the structure image from the low-resolution image is guided filtered with the structure image from the high-resolution image as the guidance image. The combination step is performed by pixel-wise addition of the filtered structure image and the texture image. Quantitative and qualitative evaluation demonstrate the proposed method preserves spectral and spatial fidelity of input images.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.2
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• pp.143-150
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• 2023

Underwater wireless communication is a challenging issue for realizing the smart aqua-farm and various marine activities for exploring the ocean and environmental monitoring. In comparison to acoustic and radio frequency technologies, the visible light communication is the most promising method to transmit data with a higher speed in complex underwater environments. To send data at a speedier rate, high-performance photodetectors are essentially required to receive blue and/or cyan-blue light that are transmitted from the light sources in a light-fidelity (Li-Fi) system. Here, we fabricated high-performance organic phototransistors (OPTs) based on P-type donor polymer (PTO2) and N-type acceptor small molecule (IT-4F) blend semiconductors. Bulk-heterojunction (BHJ) PTO2:IT-4F photo-active layer has a broad absorption spectrum in the range of 450~550 nm wavelength. Solution-processed OPTs showed a high photo-responsivity >1,000 mA/W, a large photo-sensitivity >10³, a fast response time, and reproducible light-On/Off switching characteristics even under a weak incident light. BHJ organic semiconductors absorbed photons and generated excitons, and efficiently dissociated to electron and hole carriers at the donor-acceptor interface. Printed and flexible OPTs can be widely used as Li-Fi receivers and image sensors for underwater communication and underwater internet of things (UIoTs).