• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.379-387
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• 2024

Agriculture has always been the foundation of Vietnam's economy, accounting for a significant portion of GDP. However, like many traditional industries, Vietnamese agriculture faces many challenges, from inefficient supply chains to unpredictable weather developments. In recent years, Vietnam's agricultural sector has been looking for ways to improve productivity and efficiency by applying modern technology. Among these technologies, artificial intelligence (AI) has emerged as a potential solution to address the challenges farmers and other stakeholders face in the agricultural supply chain. AI can analyze large amounts of data, optimize resource allocation, and predict market trends, which can significantly improve decision-making in agriculture. However, despite the promising prospects of AI in agriculture, there are still challenges to the widespread application of AI in Vietnam. These include the need for more awareness, technical expertise, and Infrastructure to support AI implementation. In this study, we analyze the current state of AI applications in Vietnam's agricultural supply chain, identify key challenges, and propose strategies to facilitate the integration of AI technology in agriculture supply chains in Vietnam in the digital age.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3594-3601
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• 2024

It is difficult to detect a small-scale leakage in a nuclear power plant (NPP) quickly and take appropriate action. Delaying these procedures can have adverse effects on NPPs. In this paper, we propose leak flow rate prediction using the bidirectional gated recurrent unit (Bi-GRU) method to detect leakage quickly and accurately in small-scale leakage situations because large-scale leak rates are known to be predicted accurately. The data were acquired by simulating small loss-of-coolant accidents (LOCA) or small-scale leakage situations using the modular accident analysis program (MAAP) code. In addition, to improve prediction performance, data were collected by distinguishing the break sizes in more detail. In addition, the prediction accuracy was improved by performing both LOCA diagnosis and leak flow rate prediction in small LOCA situations. The prediction model developed using the Bi-GRU showed a superior prediction performance compared with other artificial intelligence methods. Accordingly, the accurate and effective prediction model for small-scale leakage situations proposed herein is expected to support operators in decision-making and taking actions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.338-340
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• 2014

The purpose of this research is to support decision making of emergency rescue system with GIS which selects landing point of emergency rescue for emergency situation on mountains and dropping point when landing is impossible. The area of research was limited to Pocheon-si, Gyeonggi-do. The results were divided into two values; landing point of helicopter on mountains and dropping point. Digital map, forest type map and forest soil map were utilized as fundamental data. Factors of landing point were slope, topographical characteristics, vegetation characteristics and area of helicopter landing point by helicopter data. And, for dropping point, slope and vegetation characteristics were divided as factors and GIS intersect function was utilized for the analysis. But, this research was conducted by excluding factor values of wind direction, wind velocity, etc. In the future, it's necessary to improve effectiveness of the analysis more by making a connection with Meteorological Agency DB.

• Asia Marketing Journal
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• v.14 no.3
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• pp.27-48
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• 2012

Temperature and weather are all around us, quite literally. Furthermore, temperature and weather not only permeate our atmosphere, constantly affecting our visceral states of warmth and coldness, but they metaphorically permeate our language. People, products, and ideas can all be "hot" or "cold." Given this ubiquity, it is perhaps surprising that relatively little research has systematically examined the influence of temperature on choice and judgment. Temperature-related words such as "hot" and "cold" are often used to describe impulsive and calculated behaviors, respectively. These metaphoric connotations of thermal concepts raise the question as to whether temperature, psychological states and decision making are related to each other, and if so, how. The current research examines these questions and finds support for a relationship. Across one field study and one laboratory experiment, I demonstrate that both hot ambient room temperature (Spa) and hot temperature primes (words) trigger decision outcomes in line with the metaphoric association between hot temperature and impulsivity. In the field study, participants were recruited in hot (40-50 degrees Celsius) and cold (10 degrees Celsius) rooms at a spa. Participants were simply asked to indicate their willingness-to-pay (WTP) for three product categories (travel package, birthday dinner, and cell phone). The results showed that participants in the hot room in comparison to those in the cold room were willing to pay more for the same products. Next, I tested if our results would go beyond ambient temperature and would hold if I were to prime temperature concepts by using a different priming method (i.e., subliminal vs. supraliminal). In line with the previous findings in the spa, participants in the hot priming condition were more likely to choose the wrong answer for the bat and baseball question than those in the cold priming condition. In addition, product type (e.g., pleasure vs. necessity) can moderate the effect of hot temperature on impulsivity. Mood and arousal did not mediate participants' responses. My findings seem to suggest that the effects of temperature on decision outcomes can be attributed to metaphoric associations rather than incidental mood or arousal. The current research applies a novel perspective in understanding the relationship between temperature and judgment and decision making. Also, the results have practical implications for packaging, advertising, merchandising, and pricing of goods and services, as well as for public policy and awareness. One of the most natural implications of my findings would be that retailers would be better off carrying more impulse purchase items on hot days. Furthermore, point-of-purchase promotions encouraging impulse purchase is more likely to be effective in retail environments with higher temperature than with lower temperature. In addition, advertisements and product packages evoking hot temperature associations (e.g., beach, sunshine, summer) might lead consumers to pay higher price for the advertised product than those with cold temperature associations.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.1-7
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• 2020

In order to implement a smart factory for manufacturing innovation, more digital twins will be developed and applied gradually. In particular, simulation and optimization of digital twins makes it possible to support critical decision-making like a predictive maintenance of the equipment for manufacturing. In terms of a user perspective, this study suggests the conceptual framework of Digital Twin Management System (DTMS) for supporting the analytical and managerial activities for Digital Twins. We integrate the methods and structure of the area like Manufacturing Engineering, Decision Support Systems, and Optimization for developing the DTMS. The framework suggested in this study shows a typical DSS which consists of dialog management system, model management system and data management system. It also includes Analytical Digital Twins and simulations & optimization module. The framework is being applied in one of the most competitive and complex industrial sector. Also this study is meaningful to suggest a new direction of research.

• Journal of Hospice and Palliative Care
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• v.25 no.1
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• pp.12-24
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• 2022

Purpose: This descriptive study compared the perceptions, determinants, and needs of patients, family members, nurses, and physicians regarding life-sustaining treatment decisions for patients with hematologic malignancies in the hematology-oncology department of a tertiary hospital in Seoul, Korea. Methods: In total, 147 subjects were recruited, gave written consent, and provided data by completing a structured questionnaire. Data were analyzed using analysis of variance, the chi-square test, and the Fisher exact test. Results: Nurses (F=3.35) and physicians (F=3.57) showed significantly greater familiarity with the Act on Decisions on Life-Sustaining Treatment than patients (F=2.69) and family members (F=2.59); (F=19.58, P<0.001). Many respondents, including 19 (51.4%) family members, 16 (43.2%) physicians, and 11 (29.7%) nurses, agreed that the patient's opinion had the greatest effect when making life-sustaining treatment decisions. Twelve (33.3%) patients answered that mental, physical, and financial burdens were the most important factors in life-sustaining treatment decisions, and there was a significant difference among the four groups (P<0.001). Twenty-four patients (66.7%), 27 (73.0%) family members, and 21(56.8%) nurses answered that physicians were the most appropriate people to provide information regarding life-sustaining treatment decisions. Unexpectedly, 19 (51.4%) physicians answered that hospice nurse practitioners were the most appropriate people to talk to about life-sustaining treatment (P<0.001). Conclusion: It is of utmost importance that the patient and physician determine when life-sustaining treatment should be withdrawn, with the patient making the ultimate decision. Doctors and nurses have the responsibility to provide detailed information. The goal of end-of-life planning is to ensure patients' dignity and respect their values.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1135-1148
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• 2018

Previous studies on reservoir operation have been assumed that the climate in the future would be similar to that in the past. However, in the presence of climate non-stationarity, Robust Optimization (RO) which finds the feasible solutions under broader uncertainty is necessary. RO improves the existing optimization method by adding a robust term to the objective function that controls the uncertainty inherent due to input data instability. This study proposed Robust-SDP that combines Stochastic Dynamic Programming (SDP) and RO to estimate dam operation rules while coping with climate non-stationarity. The future inflow series that reflect climate non-stationarity were synthetically generated. We then evaluated the capacity of the dam operation rules obtained from the past inflow series based on six evaluation indicators and two decision support schemes. Although Robust-SDP was successful in reducing the incidence of extreme water scarcity events under climate non-stationarity, there was a trade-off between the number of extreme water scarcity events and the water scarcity ratio. Thus, it is proposed that decision-makers choose their optimal rules in reference to the evaluation results and decision support illustrations.

• Journal of Distribution Science
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• v.14 no.11
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• pp.75-82
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• 2016

Purpose - In order for actively pursuing medium and long term policies of Gangwon region to be effectively and efficiently driven, efficacious and practical development strategies are needed. In terms of regional revitalization in most regions that are dependent on the primary industry like Gangwon-do Province, the maintaining of local community becomes difficult and there are limitations on the support from the central government and local governments. Therefore, local communities need to implement measures not only to be financially independent but also maintain and activate themselves. And community business can be adopted to be a proper strategy to cope with this change. This study drew importance of a community business model appropriate for Gangwon-do region to figure out success factors. Research design, data, and methodology - This study aimed to come up with importance of community business model for Gangwon-do region by using AHP Method. AHP Method, which was developed by Professor Saaty in 1970', is a methodology to simplify complex problems for a rational decision making. A survey targeting related public officials and expert group was carried out and a total of 30 questionnaires were collected for the analysis. Results - Analysis model used in this study was to prioritize community business models of Gangwon-do region. The second hierarchy was divided according to local restoration type, local resource utilization type, environment improvement type, and life support type. The third hierarchy consisted of 5 items such as network, the middle structure, program, government support, and human resources to measure each importance. As a result, in the second hierarchy, local resource utilization type had the highest importance. In the third hierarchy, the middle structure had the highest importance, followed by government support, program, network, and human resources. Collectively, the results suggested that important critical factors of community business model of Gangwon-do region was the importance of local resource utilization model and the middle structure. Conclusions - Not only should projects that are already operating in the region but next community business projects that are planning in the Gangwon-do region should be practically operated in view of the importance and the models derived from this study.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.328-334
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• 2011

Disasters are subject to occur repeatedly ever year. Disaster relief donations are paid in terms of scale of damage. Empirical studies on this issue have not been substantially implemented, in particular, on perceptions by disaster victims and civil servants of local government. Disaster victims and civil servants of local government are seen as the key groups for the support system of disaster relief donations as the former is actual beneficiaries and the latter is to investigate concerned data on decision making for support system. In the regard, in the study, problems and improving directions for more efficient support system are analysed and suggested based on the survey of perception of disaster victims and civil servants of local government. Conclusion and some policy implications are also included in the concluding section.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2453-2458
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• 2012

Background: The healthcare needs of cancer patients are complex and persons involved in their caregiving process are faced with many issues that need to be addressed. The entire family and particularly the person taking on responsibility for patient care develop expectations from healthcare professionals, especially nurses. Objective: The study was conducted to evaluate the impact of a home education program provided to caregivers of cancer patients on the level of their perceived social support and problems in caregiving. Interventions/Methods: The caregivers of thirty seven cancer patients of 2,400 registered people in a family center were given an educational program in this descriptive and cross-sectional study twice a week for a month during the period of March 2011 - April 2011. Results: Of all caregivers, 56.8% were between the ages 36-40, 94.5% were female, 91.9% had received no education on caregiving, 81.0% stated that they mostly felt physically and mentally inadequate in their caregiving. Perceived Social Support from the family indicated a significant difference at $8.05{\pm}4.38$ before and $11.7{\pm}4.97$ after the education. A comparison of the mean scores of caregivers on emotional issues before and after the education revealed the following: spiritual distress scores were $2.54{\pm}0.69$ before and $2.44{\pm}0.43$ after the education; hopelessness scores, $2.24{\pm}0.59$ before and $2.23{\pm}0.38$ after the education; ineffective individual coping was $3.89{\pm}1.42$ before and $2.45{\pm}0.59$ after the education; competing needs in decision-making were $3.54{\pm}0.69$ before and $2.10{\pm}1.24$ after the education; depressive feeling were $3.01{\pm}1.53$ before and $2.02{\pm}0.99$ after the education (p<0.05). Conclusions: Positive effects of home education on levels of perceived social support and caregiving problems of caregivers of cancer patients were observed. Home educational programs for caregivers of cancer patients are important for both better understanding of the requirements of their patients and themselves.