• Journal of Digital Convergence
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• v.18 no.7
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• pp.111-122
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• 2020

The current study aimed to examine university students' perceptions of the positive effects of L2 oral presentations in terms of communication skills and future employment. The participants were 13 undergraduate students enrolled in L2 oral presentation classes at the beginner or intermediate level. This study followed a qualitative research approach using in-depth and semi-structured interviews as the primary method. The findings revealed that students largely exhibited the benefits of oral presentations in three ways: by enhancing L2 proficiency, building confidence in public speaking, and gaining competitive advantages in their future careers. As a challenge for L2 learners, oral presentations were considered fundamental to develop effective communication skills in academic and professional contexts.

• Journal of Gifted/Talented Education
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• v.26 no.4
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• pp.635-652
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• 2016

This study investigated operation plan for the Cyber Bridge Program based on the survey from teachers of science high schools. Teachers were found to be thinking it positive that cyber programs can be operated free from the time and spatial restrictions. They thought that teacher interactions are hard to occur and teachers' role in learning is limited as well. Also, the geographical, physical, and socio cultural minorities might have benefits from cyber programs either as regular programs or the before entrance programs. Therefore, the detailed plans are needed. Most of all, since the educational contents are the key for the programs, we suggested some contents categories and developmental criteria. As a result, the developments of high quality contents and financial supports for the successful Cyber Bridge Program are essential.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.39-39
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• 2012

Data assimilation techniques have received growing attention due to their capability to improve prediction in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modelling software are based on a deterministic approach. In this study, we developed a hydrological modelling framework for sequential data assimilation, namely MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modelling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. In this software framework, sequential data assimilation based on the particle filters is available for any hydrologic models considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and radar rainfall estimates is assessed simultaneously in sequential data assimilation.

• Health Policy and Management
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• v.22 no.4
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• pp.597-627
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• 2012

As misalignments among images, identity, and legitimacy of health professionals and institutions have been on the rise, CEOs of health care organizations have been required to enhance organizational accountability. Despite the accumulation of literature on the conceptual discussions of accountability, only a few studies empirically investigated key barriers to accountability and its facilitators. To identify perception on accountability with key barriers and facilitators of organizational accountability, a semi-structured interview with 11 CEOs of Korean hospitals was conducted. A short survey was taken to get quantitative data on CEO's perception on organizational accountability. To CEOs, accountability was very complex and unfamiliar concept, but understood as physician's code of ethics by nature and basic principle of hospital management. CEOs thought accountability could be improved through ethical leadership, financial stability and learning climate of hospitals. Distrust of the government, which failed to provide economic incentives for hospitals to increase accountability activities, was emphasized as a serious barrier to hospital accountability. There was consensus among hospital CEOs as to the importance of accountability in management. However, there were concerns that, without policy instruments to motivate hospitals toward increasing community benefits as well as collective efforts among health professionals to rebuild moral climate for being accountable, greater accountability would not be achieved in hospitals.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.353-359
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• 2021

Information technology and the need for timely and effective communication during the Covid-19 have made most governments adopt technological approaches to provide their services. E-government services have been adopted by most governments especially in developed countries to quickly and effectively share information. This study discusses the reasons why governments in the Gulf region should develop a new model for information technology knowledge management practices. To achieve this, the author identified possible benefits of adopting information technology knowledge management practices and why most governments in the Gulf find it hard to adopt them. Knowledge management allows for learning, transfer as well as sharing of information between government organizations and citizens and with the development of technology, the effectiveness of electronic services can easily be achieved. Also, effective adoption of information technology can improve knowledge management with the help of techniques that enhance capture, storage, retrieval as well as sharing of information. The author used systematic literature review to select 28 journals and articles published post 2019. IEEE, Google Scholar and Science Direct were used to select potential studies from which 722 journals and articles were selected. Through screening and eligibility assessment, 21 articles were retained while the back and forward search had 7 more articles which were also included in the study. Using information gathered from these articles and journals a new conceptual model was developed to help improve information technology knowledge management for governments in the Gulf region to effectively deliver e-services during Covid-19. This model was developed based on the process of KM, Theory of Planned Behavior and Unified Theory of Acceptance and Use of Technology. Based on the developed model. From UTAUT model, performance expectancy, effort expectancy as well as social influence had a great impact.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.153-159
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• 2022

The article discusses the use of smart technologies in the training of future specialists. Today, learning using smart technologies is becoming a new educational standard, where information is presented in a logical sequence, computer training systems have powerful functions for the educational process. The functions of smart technologies are highlighted. It is noted that smart technologies are successfully used in the field of education and professional training. The concept of "smart education" is characterized. Smart education is an educational paradigm that underlies a new type of education system. The implementation of the smart education paradigm is aimed at the process of obtaining competencies and competencies for flexible and adapted interaction with the social, economic and technological environment. Smart education should ensure that the benefits of the global information society can be used to meet educational needs and interests. A special place is occupied by computer-based educational multimedia systems that allow you to deepen your knowledge, reduce the duration of training, and increase the number of students per teacher. The main principles of smart education are highlighted. Improving the efficiency of training in a modern higher education institution is impossible without the introduction of smart technologies in the organization of the educational process.

• The Journal of Korean Medicine
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• v.43 no.3
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• pp.49-64
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• 2022

Objectives: Peer role-play (PRP) has been used in health care training simulations because standardized patient training requires considerable time and expense. This study described the implementation of clinical simulation using PRP and examined the effect. Methods: Final year students from a single college of Korean medicine engaged in PRP as part of clinical skills practice. Education tools from clinical practice guidelines were used to structure the PRP. Communication competency was assessed with the Korean Version of the Self-Efficacy Questionnaire (KSE-12). Whether this training helped to achieve graduate outcomes was evaluated on a five-point scale. Results: Fifty-nine students (53.2%) participated in the survey. Among 12 items on the KSE-12, the score for "How certain are you that you are able to successfully listen attentively to the patient?" was the highest. Further, PRP was found to be helpful for self-directed learning, establishment of one's professional identity, and the ability to communicate and manage patients. Three themes ("Benefits of role-play", "The importance of positive feedback", "Limitations and problems of role-play"), 15 categories, and 16 central meanings were derived by categorizing learners' subjective opinions about PRP. Conclusions: Study findings indicate that PRP may contribute to improving communication skills and establishing a professional identity for future Korean medicine doctors. We suggest using PRP in clinical education in colleges of Korean Medicine.

• Korean Journal of Childcare and Education
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• v.19 no.3
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• pp.19-39
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• 2023

Objective: The purpose of this study was to analyze the experiences of foreign students in childcare practicum, with a specific focus on identifying the difficulties they encountered and the values they derived from their practicum experiences. The aim was to gain insights that can contribute to improving practicum support for these students. Methods: A total of 6 foreign students were selected as participants for this study using snowball sampling. The data collection period spanned from May 2021 to March 2023, during which semi-structured interviews were conducted and qualitatively analyzed. Results: Foreign students faced challenges in securing practicum placements prior to the start of their program. Communication difficulties necessitated the use of interpreters to interact with children. Additionally, documenting information in a language other than their mother tongue posed a challenge. Consequently, there was a need for tailored training support to address the specific needs of foreign students in childcare practicum. Despite these challenges, the students reported rewarding and valuable experiences during their practicum. These experiences included discovering the teaching identity in Korea, learning about desirable practices in the field, recognizing and addressing personal shortcomings, and developing a sense of vocation for the advancement of infant education in their home countries. Conclusion/Implications: If we actively listen to and provide appropriate support for the specific needs of foreign students in their childcare practicum, they have the potential to become excellent childcare teachers who can foster a harmonious and inclusive environment within our multicultural society.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.55.3-55.3
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• 2019

We present a pipeline to estimate baryonic properties of a galaxy inside a dark matter (DM) halo in DM-only simulations using a machine trained on high-resolution hydrodynamic simulations. As an example, we use the IllustrisTNG hydrodynamic simulation of a (75 h^-1 Mpc)³ volume to train our machine to predict e.g., stellar mass and star formation rate in a galaxy-sized halo based purely on its DM content. An extremely randomized tree (ERT) algorithm is used together with multiple novel improvements we introduce here such as a refined error function in machine training and two-stage learning. Aided by these improvements, our model demonstrates a significantly increased accuracy in predicting baryonic properties compared to prior attempts --- in other words, the machine better mimics IllustrisTNG's galaxy-halo correlation. By applying our machine to the MultiDark-Planck DM-only simulation of a large (1 h^-1 Gpc)³ volume, we then validate the pipeline that rapidly generates a galaxy catalogue from a DM halo catalogue using the correlations the machine found in IllustrisTNG. We also compare our galaxy catalogue with the ones produced by popular semi-analytic models (SAMs). Our so-called machine-assisted semi-simulation model (MSSM) is shown to be largely compatible with SAMs, and may become a promising method to transplant the baryon physics of galaxy-scale hydrodynamic calculations onto a larger-volume DM-only run. We discuss the benefits that machine-based approaches like this entail, as well as suggestions to raise the scientific potential of such approaches.

• Structural Engineering and Mechanics
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• v.85 no.4
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• pp.469-484
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• 2023

A deep recursive bidirectional Cuda Deep Neural Network Long Short Term Memory (Bi-CuDNNLSTM) layer is recruited in this paper to predict the entire force time histories, and the corresponding hysteresis and backbone curves of reinforced concrete (RC) bridge piers using experimental fast and slow cyclic tests. The proposed stacked Bi-CuDNNLSTM layers involve multiple uncertain input variables, including horizontal actuator displacements, vertical actuators axial loads, the effective height of the bridge pier, the moment of inertia, and mass. The functional application programming interface in the Keras Python library is utilized to develop a deep learning model considering all the above various input attributes. To have a robust and reliable prediction, the dataset for both the fast and slow cyclic tests is split into three mutually exclusive subsets of training, validation, and testing (unseen). The whole datasets include 17 RC bridge piers tested experimentally ten for fast and seven for slow cyclic tests. The results bring to light that the mean absolute error, as a loss function, is monotonically decreased to zero for both the training and validation datasets after 5000 epochs, and a high level of correlation is observed between the predicted and the experimentally measured values of the force time histories for all the datasets, more than 90%. It can be concluded that the maximum mean of the normalized error, obtained through Box-Whisker plot and Gaussian distribution of normalized error, associated with unseen data is about 10% and 3% for the fast and slow cyclic tests, respectively. In recapitulation, it brings to an end that the stacked Bi-CuDNNLSTM layer implemented in this study has a myriad of benefits in reducing the time and experimental costs for conducting new fast and slow cyclic tests in the future and results in a fast and accurate insight into hysteretic behavior of bridge piers.