• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.47.3-48
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• 2021

We studied the large scale dynamo process in a system forced by helical magnetic field. The dynamo process is basically nonlinear, but can be linearized with 𝛼&𝛽 coefficients and large scale magnetic field $\bar{B}$. This is very useful to the investigation of solar (stellar) dynamo. A coupled semi-analytic equations based on statistical mechanics are used to investigate the exact evolution of 𝛼&𝛽. This equation set needs only magnetic helicity ${\bar{H}}_M({\equiv}{\langle}{\bar{A}}{\cdot}{\bar{B}}{\rangle},\;{\bar{B}}={\nabla}{\times}{\bar{A}})$ and magnetic energy ${\bar{E}}_M({\equiv}{\langle}{\bar{B}}^2{\rangle}/2)$. They are fundamental physics quantities that can be obtained from the dynamo simulation or observation without any artificial modification or assumption. 𝛼 effect is thought to be related to magnetic field amplification. However, in reality the averaged 𝛼 effect decreases very quickly without a significant contribution to ${\bar{B}}$ field amplification. Conversely, 𝛽 effect contributing to the magnetic diffusion maintains a negative value, which plays a key role in the amplification with Laplacian ∇²(= - k²) for the large scale regime. In addition, negative magnetic diffusion accounts for the attenuation of plasma kinetic energy E_V(= 〈 U² 〉/2) (U: plasma velocity) when the system is saturated. The negative magnetic diffusion is from the interaction of advective term - U • ∇ B from magnetic induction equation and the helical velocity field. In more detail, when 'U' is divided into the poloidal component U_pol and toroidal one U_tor in the absence of reflection symmetry, they interact with - B • ∇ U and - U • ∇ B from ∇ × 〈 U × B 〉 leading to 𝛼 effect and (negative) 𝛽 effect, respectively. We discussed this process using the theoretical method and intuitive field structure model supported by the simulation result.

• Journal of Digital Convergence
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• v.21 no.1
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• pp.19-27
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• 2023

This is an implementation study towards the development of a strategy to improve the pneumonia adequacy evaluation index of regional public hospital and to confirm its effectiveness. One physician, eight nurses, one computer room staff, and one nursing professor working at a regional base public hospital located in N city participated in this study from March to October 2021. An implementation study was conducted based on the conceptual model of Zuber-Skerritt & Fletcher. The stages of planning, implementation, evaluation, and reflection were operated in two cycles, and the effectiveness was evaluated in the second and third quarters. Compared to the pneumonia adequacy evaluation index in 2019, all indicators reached 100% of the standard target in 2021. The results of this study therefore infer that to provide higher quality medical services in the future, it is necessary to apply medical quality improvement activities through practical research under multidisciplinary participation and cooperation and to review the applicability of clinical sites.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.191-199
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• 2023

In this paper, we propose a method to extract the features of five sensor-only facilities built as infrastructure for autonomous cooperative driving, which are from point cloud data acquired by LiDAR. In the case of image acquisition sensors installed in autonomous vehicles, the acquisition data is inconsistent due to the climatic environment and camera characteristics, so LiDAR sensor was applied to replace them. In addition, high-intensity reflectors were designed and attached to each facility to make it easier to distinguish it from other existing facilities with LiDAR. From the five sensor-only facilities developed and the point cloud data acquired by the data acquisition system, feature points were extracted based on the average reflective intensity of the high-intensity reflective paper attached to the facility, clustered by the DBSCAN method, and changed to two-dimensional coordinates by a projection method. The features of the facility at each distance consist of three-dimensional point coordinates, two-dimensional projected coordinates, and reflection intensity, and will be used as training data for a model for facility recognition to be developed in the future.

• Journal of Korean Academy of Nursing
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• v.53 no.6
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• pp.652-665
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• 2023

Purpose: This study aimed to develop a nursing clinical judgment scale (NCJS) and verify its validity and reliability in assessing the clinical judgment of nurses. Methods: A preliminary instrument of the NCJS comprising 38 items was first developed from attributes and indicators derived from a literature review and an in-depth/focus interview with 12 clinical nurses. The preliminary tool was finalized after 7 experts conducted a content validity test based on a data from a preliminary survey of 30 hospital nurses in Korea. Data were collected from 443 ward, intensive care unit, emergency room nurses who voluntarily participated in the survey through offline and online for the verification of the construct validity and reliability of the scale. Results: The final scale comprised 23 items scored on a 5-point Likert scale. Six factors - integrated data analysis, evaluation and reflection on interventions, evidence on interventions, collaboration among health professionals, patient-centered nursing, and collaboration among nurse colleagues - accounted for 64.9% of the total variance. Confirmatory factor analysis supported the fit of the measurement model, comprising six factors (root mean square error of approximation = .07, standardized root mean square residual = .04, comparative fit index = .90). Cronbach's α for all the items was .92. Conclusion: The NCJS is a valid and reliable tool that fully reflects the characteristics of clinical practice, and it can be used effectively to evaluate the clinical judgment of Korean nurses. Future research should reflect the variables influencing clinical judgment and develop an action plan to improve it.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.105-112
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• 2024

In contemporary society, the expression of emotions and self-reflection are considered pivotal factors with a positive impact on stress management and mental well-being, thereby highlighting the significance of journaling. However, traditional journaling methods have posed challenges for many individuals due to constraints in terms of time and space. Recent rapid advancements in chatbot and emotion analysis technologies have garnered significant attention as essential tools to address these issues. This paper introduces an artificial intelligence chatbot that integrates the GPT-3 model and emotion analysis technology, detailing the development process of a system that automatically generates journals based on users' chat data. Through this system, users can engage in journaling more conveniently and efficiently, fostering a deeper understanding of their emotions and promoting positive emotional experiences.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.23-29
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• 2024

In this paper, we propose a fast GPU-based method for representing pore flow, absorption, emission, and diffusion effects represented by cloth-liquid interactions using smoothed particle hydrodynamics (SPH), a particle-based fluid solver: 1) a unified framework for GPU-based representation of various physical effects represented by cloth-liquid interactions; 2) a method for efficiently calculating the saturation of a node based on SPH and transferring it to the surrounding porous particles; 3) a method for improving the stability based on Darcy's law to reliably calculate the direction of fluid absorption and release; 4) a method for controlling the amount of fluid absorbed by the porous particles according to the direction of flow; and finally, 5) a method for releasing the SPH particles without exceeding their maximum mass. The main advantage of the proposed method is that all computations are computed and run on the GPU, allowing us to quickly model porous materials, porous flows, absorption, reflection, diffusion, etc. represented by the interaction of cloth and fluid.

• Journal of vocational education research
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• v.30 no.4
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• pp.23-49
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• 2011

Faculty performance evaluation system has been settled down as an uncomfortable but unavoidable system, and it is one of the most important factors to grow the college competitiveness up. In this study, we selected and surveyed faculty evaluation models of several universities and colleges in Korea, and analyzed by comparing each evaluation areas of educational achievement, college-industry collaboration, research, and service. We also identified the properties of the current faculty evaluation models of the junior colleges, and derived several problems from these models such as an imitation of four-year university model, a disorders of job evaluation with respect to the attributes of classified jobs, a large variation of individual item weights, and an insufficient reflection of major characteristics. Based on these surveys and analysis, an improved faculty evaluation model for the junior college is proposed in this study. This model proposed four basic areas-educational achievement, college-industry collaboration, research, and service by considering the importance of the college-industry collaboration in the junior college-as well as the team evaluation area. Weights of the SCI-class paper was selected as a criterion for the arrangement of objective comparison of each evaluation items. We showed the integration method of several different evaluation model with respect to the attributes of classified jobs of each faculties, and evaluation plan of variational characteristics according to the majors of individuals in this model. Finally, we introduced an area fail and rating system to operate efficiently the proposed faculty evaluation model.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

• Information Systems Review
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• v.13 no.3
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• pp.141-163
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• 2011

The advancement of information technologies including the Internet has affected the way of social information processing as well as brought about the paradigm shift to the information society. Accordingly, it is very important to study the process of social information processing over the digital media through which social information is generated, distributed, and led to social consensus. In this study, we analyze the mechanism of social information processing, identify a process model of social consensus and institutionalization of the results, and finally propose a set of information processing characteristics on the internet media. We deploy the ethnographic approach to analyze the meaning of group behavior in the context of society to analyze two major events which happened in Korean society. The formation process of social consensus is found to consist of 5 steps: suggestion of social issues, selective reflection on public opinion, acceptance of the issues and diffusion, social consensus, and institutionalization and feedback. The key characteristics of information processing in the Internet is grouped into proactive response to an event, the changes in the role of opinion leader, the flexibility of proposal and analysis, greater scalability, relevance to consensus making, institutionalization and interaction. This study contributes to the literature by proposing a process model of social information processing which can be used as the basis for analyzing the social consensus making process from the social network perspective. In addition, this study suggests a new perspective where the utility of the Internet media can be understood from the social information processing so that other disciplines including politics, communications, and management can improve the decision making performance in utilizing the Internet media.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.25-41
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• 2011

AVO analysis was conducted on hydrocarbon-bearing structures by applying the crossplot and offset-coordinate amplitude polynomial techniques. To evaluate the applicability of the AVO analysis, it was conducted on synthetic data that were generated with an anticline model, and field data from the hydrocarbon-bearing Colony Sand bed in Canada. Analysis of synthetic data from the anticline model demonstrates that the crossplot method yields zero-offset reflection amplitude and amplitude variation with negative values for the upper interface of the hydrocarbon-bearing layer. The crossplot values are clustered in the third quadrant. The results of AVO analysis based on the coefficients of the amplitude polynomial are similar to those from the crossplots. These well correlated results of AVO analysis on field and synthetic data suggest that both methods successfully investigate the characteristics of the reflections from the upper interface of a hydrocarbon-bearing layer. Analysis based on the incident-angle equation facilitates the application of various interpretation methods. However, it requires the conversion of seismic data to an incident angle gather. By contrast, analysis using coefficients of the amplitude polynomial is cost-effective because it allows examining amplitude variation with offset without involving the conversion process. However, it warrants further investigation into versatile application. The two different techniques can be complement each other effectively as AVO-analysis tools for the detection of hydrocarbon reservoirs.