• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.283-295
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• 2016

The purpose of this study is to analyze the conditions of disability facilities in universities and to improve disability facilities for disabled students. First, we selected six universities in Jeollabukdo and categorized their accommodations into exterior connection facilities, interior facilities, sanitation facilities, guidance facilities, and other facilities. We evaluated their fidelity to guidelines on accommodations under the convenience enhancement act for students with disabilities. The physical environment of the universities generally did not fit the guidelines, and they did not provide an appropriate environment for students because of inconvenient utilization and lack of management, even though they were equipped. Universities should make a greater effort to improve and expand the accommodations to establish a consumer-centered higher-education environment. This can be done by universal design and enhancing the fidelity for an advanced higher-education environment and students with disabilities.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.509-515
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• 2022

To comparison of the differences in affecting factors of prevalence of obesity and hypertension according to the employment type of single-person households, aged 20 to 59 years old people were classified by permanent and temporary workers(n=566). A questionnaire survey was conducted by purposive quota sampling to ask disease, income and health habits. In the results of logistic regression on hypertension and obesity, the prevalence of hypertension was significantly affected as age and obesity increased regardless of employment type. In particular, temporary workers with lower income were more likely to have hypertension(p<0.001). The prevalence of obesity was significantly lower for female than for male regardless of employment type. In particular, temporary workers had a higher prevalence of obesity as their dinner fidelity decreased(p<0.001). As a result, chronic disease management for single-person households with lower income and dinner fidelity should be intervened in more useful ways.

• Journal of Industrial Convergence
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• v.22 no.8
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• pp.73-83
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• 2024

The study attempted to examine the effects of hybrid simulation practice program on critical thinking disposition, self-efficacy, communication competency, and clinical competency of nursing students. The study was one group pre-test and post-test design. Data were collected between April 24 to May 5, 2023 from 35 nursing students. The collected data was analyzed using the SPSS 25.0 program, frequency analysis, mean, standard deviation, and paired t-test. Research results showed that nursing students' critical thinking disposition(t=7.01, p<.001), self-efficacy(t=2.17, p=.037), communication competency(t=2.70, p=.011), and clinical competency(t=6.60, p<.001) were improved after the simulation program. The hybrid simulation practice program is significant in that it applies various learning tools, including high-fidelity-low-fidelity-role play to strengthen the connection between nursing students' theory and practice.

• The Journal of Industrial Distribution & Business
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• v.11 no.11
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• pp.19-28
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• 2020

Purpose: The supply of and demand for medical services continue to increase as the current social environment changes. Consequently, competition among medical institutions is intensifying and hospitals must establish appropriate management strategies to improve the medical services they provide. This study suggests that the authenticity of doctors is a factor in improving medical-service quality and examines the effect authenticity has on the affective trust and satisfaction of patients. Design, methodology, and approach: The study utilized previous studies to examine the significance of potential variables, established hypotheses and used a questionnaire to confirm these hypotheses. The questionnaire was distributed to patients who had visited a hospital in the previous six months. Responses were analyzed empirically using structural equation modeling. Findings: The analysis found that a physician's authenticity has a significant impact on the affective trust of patients. While patients' affective trust does not have a similar strong impact on patient satisfaction, physician authenticity does have a significant impact on patient satisfaction. Conclusion and implications: This study examined the roles of authenticity, affective trust, and patient satisfaction in doctor-patient relationships in the medical services field. The implication of the findings is that physician authenticity is a prerequisite for patient satisfaction of medical services.

• Korean Journal of Health Education and Promotion
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• v.33 no.4
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• pp.79-87
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• 2016

Objectives: This study aims to identify participants-focused health education approaches for the management of metabolic syndrome. Methods: Data for metabolic parameters of 855,282 Koreans in 2012 were extracted and analysed from the data base of Korea Association of Health Promotion. Literature and documents including study protocols, program contents, evaluation reports and published articles were reviewed in relation to increasing effectiveness and efficiency of health education for managing metabolic syndrome. Results: Health education program should be based on participants-focused perspectives, in which clients' demographic characteristics, composition patterns of metabolic risk factors, and readiness of change are appreciated. Development of theory-based strategies for healthy behavior change and evidence-based program components are also important factors in designing and conducting health education intervention. Multiple health behavior intervention can offer a new paradigm for more comprehensive and efficient health education. Implementation fidelity needs to be systematically evaluated and strengthened to improve the validity of the health education efforts. Conclusion: Enhancing participants-focused health education is the responsibility of health education specialists in promoting the management of metabolic syndrome.

• 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.

• Information and Communications Magazine
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• v.30 no.10
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• pp.79-85
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• 2013

By interacting with external wireless sensors, smartphones can gather high-fidelity data on the surrounding environment to develop various environment-aware, personalized applications. In this work we introduce the sensor virtualization module (SVM), which virtualizes external sensors so that smartphone applications can easily utilize a large number of external sensing resources. Implemented on the Android platform, our SVM simplifies the management of external sensors by abstracting them as virtual sensors to provide the capability of resolving conflicting data requests from multiple applications and also allowing sensor data fusion for data from different sensors to create new customized sensors elements. We envision our SVM to open the possibilities of designing novel personalized smartphone applications.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1138-1143
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• 2013

In this paper, we propose a smartphone application based on a wireless fidelity(WiFi) in order to control the charging of electric vehicle(EV) and monitor the charging status together with the vehicle history information. The driver obtains much information on vehicle status through a smartphone application which communicates with the electric vehicle supply equipment(EVSE) management server while the EV also communicates with the EVSE for the authentification through controller area network(CAN). We also implement the simulator for the EV charging control system to verify the functions of the proposed application where the simulator consists of an EV model, an EVSE, and a smartphone. It is shown by the simulator that the proposed smartphone application allows the driver to control and to monitor the charging process of an EV conveniently and, moreover, it can provide the driver with vehicle information stored in the EVSE management server.

• Structural Engineering and Mechanics
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• v.69 no.1
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• pp.21-31
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• 2019

Optimizing composite structures to exploit their maximum potential is a realistic application with promising returns. In this research, simultaneous maximization of the fundamental frequency and frequency separation between the first two modes by optimizing the fiber angles is considered. A high-fidelity design optimization methodology is developed by combining the high-accuracy of finite element method with iterative improvement capability of metaheuristic algorithms. Three powerful nature-inspired optimization algorithms viz. a genetic algorithm (GA), a particle swarm optimization (PSO) variant and a cuckoo search (CS) variant are used. Advanced memetic features are incorporated in the PSO and CS to form their respective variants-RPSOLC (repulsive particle swarm optimization with local search and chaotic perturbation) and CHP (co-evolutionary host-parasite). A comprehensive set of benchmark solutions on several new problems are reported. Statistical tests and comprehensive assessment of the predicted results show CHP comprehensively outperforms RPSOLC and GA, while RPSOLC has a little superiority over GA. Extensive simulations show that the on repeated trials of the same experiment, CHP has very low variability. About 50% fewer variations are seen in RPSOLC as compared to GA on repeated trials.

• Korean Journal of Agricultural Science
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• v.48 no.2
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• pp.311-331
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• 2021

Climate change with extreme hydrological events has become a significant concern for agricultural water systems. Climate change affects not only irrigation availability but also agricultural water requirement. In response, adaptation strategies with soft and hard options have been considered to mitigate the impacts from climate change. However, their implementation has become progressively challenging and complex due to the interconnected impacts of climate change with socio-economic change in agricultural circumstances, and this can generate more uncertainty and complexity in the adaptive management of the agricultural water systems. This study was carried out for the agricultural water supply system in Seongju dam watershed in Seonju-gun, Gyeongbuk in South Korea. The first step is to identify system disturbances. Climate variation and socio-economic components with historical and forecast data were investigated Then, as the second step, problematic trends of the critical performance were identified for the historical and future climate scenarios. As the third step, a system structure was built with a dynamic hypothesis (causal loop diagram) to understand Seongju water system features and interactions with multiple feedbacks across system components in water, agriculture, and socio-economic sectors related to the case study water system. Then, as the fourth step, a mathematical SD (system dynamics) model was developed based on the dynamic hypothesis, including sub-models related to dam reservoir, irrigation channel, irrigation demand, farming income, and labor force, and the fidelity of the SD model to the Seongju water system was checked.