• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.11-21
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• 2022

The perspectives on aging women's financial security during their retirement years are based on their behavior, planning, and decision-making processes during their working years. Elderly women are considered vulnerable and have a longer life expectancy, lower-income, and limited financial understanding compared to males; therefore, drastic steps need to be taken to improve their financial stability and quality of life. The current study sought to determine the most important contributors to retired women's financial health by measuring the value of four factors/variables: capability, opportunity, willingness, and biopsychosocial. This study used a mixed model approach, with qualitative analysis in the first phase involving a focus group discussion session, a pilot analysis, and quantitative analysis for phase two involving the distribution and collection of questionnaires completed by retired women. The surveys were distributed across Malaysia in five distinct zones and yielded 339 usable replies to support the theory. The outcomes of the Multiple Regression Analysis in Malaysia revealed that capability, opportunity, and biopsychosocial factors are significant predictors of retired women's financial security, whereas the willingness indicator lacked statistical significance.

• Fisheries and Aquatic Sciences
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• v.24 no.11
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• pp.341-350
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• 2021

The energy production of offshore wind farms plays an important role in expanding renewable energy. However, the development of offshore wind farms faces many challenges due to its incompatibility with marine environments and its social acceptability among the local community. In this study, we reviewed the marine environmental impact assessment status of offshore wind farm development projects for 2012-2019 in South Korea. A total of nine projects were selected for this study, all of which experienced considerable conflict with local fisheries resources. To appropriately respond to the underlying challenges faced by offshore wind farm development and in order to better support decision-making for future impact assessment, our findings identified: i) a need for adequate preliminary investigation and technical examination of fisheries resources; ii) a need to assess and estimate the impact of underwater noise, vibration, and electromagnetic waves on fisheries resources during wind farm construction and operation; and iii) a need for a bottom-up approach that allows for communication with local stakeholders and policy-makers to guarantee the local acceptability of the development.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2859-2870
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• 2022

Because nuclear power plants (NPPs) are safety-critical infrastructure, it is essential to increase their safety and minimize risk. To reduce human error and support decision-making by operators, several artificial-intelligence-based diagnosis methods have been proposed. However, because of the nature of data-driven methods, conventional artificial intelligence requires large amount of measurement values to train and achieve enough diagnosis resolution. We propose a graph neural network (GNN) based accident diagnosis algorithm to achieve high diagnosis resolution with limited measurements. The proposed algorithm is trained with both the knowledge about physical correlation between components and measurement values. To validate the proposed methodology has a sufficiently high diagnostic resolution with limited measurement values, the diagnosis of multiple accidents was performed with limited measurement values and also, the performance was compared with convolution neural network (CNN). In case of the experiment that requires low diagnostic resolution, both CNN and GNN showed good results. However, for the tests that requires high diagnostic resolution, GNN greatly outperformed the CNN.

• Korean Medical Education Review
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• v.24 no.3
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• pp.193-204
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• 2022

One of the important roles of medical schools is to support medical students in deciding upon their future career path or choosing their specialty. The purpose of this study is to suggest a career advising model and strategies for medical students through a systematic approach. This study consists of three parts. The first part introduces some main career theories: super's career development theory, career decision-making theory, social cognitive career theory, and ecosystem theory. The second part proposes a systematic career advising model using the results acquired from previous studies and theories. This model considers a medical school as a social system that consists of two domains (internal and external). This social system is considered as a complex where various factors interact with each other: students' individual characteristics, institutional policies and culture, curriculum and learning experience, students' perceived specialty characteristics, and aspects of the external environment such as healthcare systems. The third part suggests some career advising strategies based on a systematic approach that medical schools can apply. These research results can be used for designing career advising courses for medical students, integrating various career advising programs and resources of medical schools, and evaluating the outcomes of career advising programs at an institutional level.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.251-259
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• 2022

This study investigates the impact of ownership structures and audit quality on carbon emission disclosure. It also examines how audit quality affects the relationship between ownership structures and carbon emission disclosure. This research includes 106 standalone sustainability reports from non-financial companies that were listed on the Indonesia Stock Exchange (IDX) between 2015 and 2018. Our findings show that family and concentrated ownerships convey less information about carbon emissions. Our results fail to demonstrate that disclosure of carbon emissions could be a corporation's approach to respond to stakeholder pressure and public visibility and to provide legitimacy for its existence. We also find a positive and significant association between high-quality (Big4) auditors and carbon emission performance. Our further result suggests that Big4 auditors seem to compromise their high standard quality on auditing family and concentrated ownership firms. They fail to influence their family and concentrated ownership clients to be socially responsible. Policymakers should support the existence of Big4 auditors as a driver of carbon emission performance. Top management should be proactive to tackle carbon emission issues by adopting stakeholder-driven mechanisms and establishing legitimacy with society. Nevertheless, the involvement of family and highly concentrated shareholders in decision-making processes and information disclosure should not be encouraged.

• Geomechanics and Engineering
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• v.28 no.1
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• pp.65-75
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• 2022

Time and cost of construction are key factors in decision-making during a tunnel project's planning and design phase. Estimations of time and cost of tunnel construction projects are subject to significant uncertainties caused by uncertain geotechnical and geological conditions. The Gaussian Process Regression (GPR) technique for predicting ground condition and construction time and cost of mountain tunnel projects is used in this work. The GPR model is trained with data from past mountain tunnel projects. The model is applied to a case study in which the predicted time and cost of tunnel construction using the GPR model are compared with the actual construction time and cost for model validation and reducing the uncertainty for the future projects. In addition, the results obtained from the GPR have been compared with to other models of artificial neural network (ANN) and support vector regression (SVR) that the GPR model provides more accurate results.

• Korean Journal of Occupational Health Nursing
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• v.31 no.2
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• pp.66-76
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• 2022

Purpose: This study aimed to explore the constructs and context of hospital nurses' organizational silence. Methods: In-depth interviews were conducted with 17 nurses in small-middle general hospitals as well as big university hospitals. We then derived the key themes using grounded theory method. Results: Nine themes and 30 sub-themes were derived: "Willing to be recognized for performance rather than saying", "Getting used to the hard-to-speak climate", "Face the reality that does not change when said", "Complicated situation that prevents self-regulating decision-making", "Conflicts that are difficult to confront", "Unfair responsibilities that I want to evade", "Leaders who don't support me", and "Being blocked in communication". Consequently, the nurses learned to adopt a climate of silence and "learned organizational silence" behavior. They experienced that prosocial silence was essential for obtaining approval as a member of the group, and defensive silence for protecting themselves in the hierarchical structure and unfair responsibilities. Acquiescent silence originated from a futile relationship with their supervisors, one-way communications, and the unsupportive management system, in which three types of silence appeared sequentially or in combination with each other. Conclusion: Based on these results, nursing managers should identify the context of nurses' organizational silence and should lessen these silence behaviors.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.90-98
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• 2022

On February 12, 2019, the U.S. Department of Defense newly established and announced the "Defense AI Strategy" to accelerate the use of artificial intelligence (AI) technology for military purposes. As China and Russia invested heavily in AI for military purposes, the U.S. was concerned that it could eventually lose its advantage in AI technology to China and Russia. In response, China and Russia, which are hostile countries, and especially China, are speeding up the development of new military theories related to the overall construction and operation of the Chinese military based on AI. With the rapid development of AI technology, major advanced countries such as the U.S. and China are actively researching the application of AI technology, but most existing studies do not address the special topic of defense. Fortunately, the "Future Defense 2030 Technology Strategy" classified AI technology fields from a defense perspective and analyzed advanced overseas cases to present a roadmap in detail, but it has limitations in comparing private technology-oriented benchmarking and AI technology's maturity level. Therefore, this study tried to overcome the limitations of the "Future Defense 2030 Technology Strategy" by comparing and analyzing Chinese and U.S. military research cases and evaluating the maturity level of military use of AI technology, not AI technology itself.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.507-513
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• 2022

This study developed a model for predicting the number of VOD uses of IPTV, an online market in the film industry. A machine learning-based prediction model was established using the VOD usage data collected by the Korean Film Council from 2017 to 2021. Through literature research and cluster analysis, the difference between the offline market and the online market is revealed, and a new category of VOD usage is proposed. The purpose is to help IPTV companies establish marketing strategies as well as support decision-making by developing a machine learning-based VOD usage prediction model.

• Journal of Hospice and Palliative Care
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• v.26 no.1
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• pp.22-25
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• 2023

Although most patients prefer dying at home, patients whose condition rapidly becomes critical need care in the intensive care unit (ICU), and it is rare for them to die at home with their families. Therefore, interest in hospice and palliative care for patients in the ICU is increasing. Hospice and palliative care (PC) is necessary for all patients with life-threatening diseases. The following patients need palliative care in the ICU: patients with chronic critical illnesses who need tracheostomy, percutaneous gastrostomy tube, and extracorporeal life support; patients aged 80 years or older; stage 4 cancer patients; patients with specific acute diseases with a poor prognosis (e.g., anoxic brain injury and intracerebral hemorrhage requiring mechanical ventilation); and patients for whom the attending physician expects a poor prognosis. There are two PC models-a consultative model and an integrative model-in the ICU setting. Since these two models have advantages and disadvantages, it is necessary to apply the model that best fits each hospital's circumstances. Furthermore, interdisciplinary decision-making between the ICU care team and PC specialists should be strengthened to increase the provision of hospice and palliative care services for patients expected to have poor outcomes and their families.