• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.301-308
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• 2018

This paper presents an optimal design method of a hybrid structural control system considering multi-hazard. Unlike a typical structural control system in which one system is designed for one specific type of hazard, a simultaneous optimal design method for both active and passive control systems is proposed for the mitigation of seismic and wind induced vibration responses of structures. As a numerical example, an optimal design problem is illustrated for a hybrid mass damper(HMD) and 30 viscous dampers which are installed on a 30 story building structure. In order to solve the optimization problem, a self-adaptive Harmony Search(HS) algorithm is adopted. Harmony Search algorithm is one of the meta-heuristic evolutionary methods for the global optimization, which mimics the human player's tuning process of musical instruments. A self-adaptive, dynamic parameter adjustment algorithm is also utilized for the purpose of broad search and fast convergence. The optimization results shows that the performance and effectiveness of the proposed system is superior with respect to a reference hybrid system in which the active and passive systems are independently optimized.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.93-99
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• 2019

The purpose of this study is to examines the factors influencing college students' adaptation to College life adaptation, and to investigate the relationship between relationship between variables and College life adaptation. Structured questionnaire was given on 210 freshman, and data was analyzed using SPSS/WIN 22.0. There was a significant correlation between College life adaptation and Department satisfaction (r = .216, p <.001) and Ego identity (r = 395, p <.001). As a result of the statistical significance of the model predicted to College life adaptation, the F statistic value is 12.222 and the significance probability is .000. Variables have significant explanations for college adjustment at a significance level of 0.1. College life adaptation is also explained by 44% variable. If we develop the adaptation program for college life considering variables, it is expected that it will have a positive effect on the improvement of adaptation ability of college students.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.139-146
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• 2019

The purpose of this study is to find meaning of male nurses's adaptation to female nurses by grsping deeply what the adaption process of male nurses is from male nurses's point of views. What is the adaptation of male nurses to female nurses? With this research subject, we explored the adaptation process of male nurses to female nurses through phenomenological method. The study participants were 12 male nurses with more than 25 months of experience working in hospitals who agreed to the intention and method of the study. The results of this study were derived from 39 meanings of composition, 13 theme bundles, and 4 categories. As for the category, it was revealed that, in the case of maladjustment situation, there was a tendency to assimilate into force, interpersonal relationship, to improve the job ability, and to become a dedicated nurse. The results of this study can be used as basic data to develop effective nursing workforce management measures in the clinical field by understanding the adaptation process to female nurses of male nurses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.499-506
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• 2021

The purpose of this study is to verify the effect of SNS addiction on cyber-bullying among adolescents, considering the adjustment effect of friendship on this relationship. This study involved 811 middle/high school students with a gender distribution of 391 males and 420 females. According to the analysis, the higher the level of SNS addiction, the higher the level of cyber-bullying. A hierarchical regression analysis was conducted to verify the moderating effect of friendship. The result shows that better peer communication and reliance lowers the impact of cyber-bullying from SNS addiction. Based on research results suggesting the popularization of proactive pre-diagnosis programs to solve SNS addiction, practical intervention plans and the limitations of research on SNS addiction and cyber-bullying in youth are suggested.

• Journal of Nutrition and Health
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• v.54 no.2
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• pp.152-164
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• 2021

Purpose: This study aimed to examine the association between depression and eating behavior factors in Korean adults. Methods: Study subjects were selected (n = 5,103) from the participants of the 7th Korea National Health and Nutrition Examination Survey 2018 and divided into depression (men, 59; women, 162) and normal groups (men, 2,083; women, 2,799). Subjects with a Patient Health Questionnaire 9 score ≥ 10 (out of 27 points) were defined as having depression. Results: A higher prevalence of depression was observed in both men and women who were unemployed (p < 0.001, p = 0.008), had lower income (both p < 0.001), poorer subjective health (both p < 0.001), and poor food safety (both p < 0.001). The prevalence of depression was higher in women with lower education levels (p = 0.008), who were unmarried (p = 0.010), smokers (p < 0.001), and in a one-person household (p = 0.001). Obese men showed a higher prevalence of depression (p = 0.009). Men who were eating alone or skipping lunch had a high prevalence of depression (p = 0.009), while women who were eating breakfast (p = 0.012), lunch (p = 0.001), and dinner (p = 0.010) alone had a high prevalence of depression. The relationship analysis between men and women according to dietary habits using logistic regression showed that, in women, after variable adjustment, skipping lunch (odds ratio [OR], 2.677; 95% confidence interval [CI], 1.090-6.574), meal frequency of 2 times per day (OR, 1.658; 95% CI, 1.084-2.536), and lunch frequency of 3-4 times per week (OR, 3.143; 95% CI, 1.725-5.728) were significantly associated with a higher prevalence of depression. Conclusion: Depression in women was not only affected by more sociodemographic variables but also associated with decreased frequency of lunch and dinner, especially with skipping lunch.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.51-58
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• 2021

Women are reported to have increased risk of metabolic syndrome after menopause. Nevertheless, there is a lack of study on the convergent association between breast-feeding, bone mineral density(BMD) and metabolic syndrome due to women's childbirth. In this study, the data of 939 elderly women using raw data from the fifth Korean National Health and Nutrition Examination Survey(KNHANES V-1 and 2) in 2010 and 2011 were analyzed. The correlation between breast-feeding children, BMD and metabolic syndrome was analyzed by dividing them into three groups based on the number of breast-feeding children. As a result of the analysis, no specific association was found between risk factors of metabolic syndrome and BMD according to the increase in the number of breast-feeding children after adjustment for confounders. However, elderly women with a large number of breast-feeding children showed a significant association with more risk factors of metabolic syndrome. These findings can be used as a basic material for the prevention and diagnosis of metabolic syndrome and health care in elderly women.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.291-295
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• 2022

The transition to wartime operational control during the term of office, which was the promise of the Moon Jae Inn administration, fell through. More than 70 years after it was transferred during the Korean War in 1950, the policy of converting wartime operational control has been repeatedly decided and reversed several times. This conversion of wartime operational control is a national policy directly related to our security, and it is most important to understand the determinants of the administration's conversion to wartime operational control. This paper selects two cases of adjustment of wartime operational control policy during the Lee Myung Bak administration in 2006 and 2010 during the Roh Moo Hyun administration as the subject of the study and expects to gain not only policy predictive power but also successful policy execution at the time of the two administration' policy changes.

• KNOM Review
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• v.22 no.3
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• pp.25-30
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• 2019

For meteorological applications, meaningful results must be derived and provided within time and resource limits. Forecasts through numerous historical data are time-consuming and still have resource limitations in the case of disaster safety-related analyses/predictions such as local typhoon forecasts. Suitable forecasts should be provided without any problems caused by limited physical environmental conditions and when results are to be drawn under time constraints, such as typhoon forecasts and forecast services for flooded areas by road. In this paper, we analyze the application of weather and climate forecasting to provide a suitable forecasting service in both temporal and resource conditions. Through the analysis of execution time according to mesh sizes, it was confirmed that a mesh adjustment can cope with the case of the temporal constraint. In addition, by analyzing the execution time through memory resource control, we confirmed the minimum resource condition that does not affect the performance and the resource usage pattern of the application through the swap and mlock analysis.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.11-20
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• 2024

Among the generative models in Artificial Intelligence (AI), especially Generative Adversarial Network (GAN) has been successful in various applications such as image processing, density estimation, and style transfer. While the GAN models including Conditional GAN (CGAN), CycleGAN, BigGAN, have been extended and improved, researchers face challenges in real-world applications in specific domains such as disaster simulation, healthcare, and urban planning due to data scarcity and unstable learning causing Image distortion. This paper proposes a new progressive learning methodology called Progressive Step Training (PST) based on the Auxiliary Classifier GAN (ACGAN) that discriminates class labels, leveraging the progressive learning approach of the Progressive Growing of GAN (PGGAN). The PST model achieves 70.82% faster stabilization, 51.3% lower standard deviation, stable convergence of loss values in the later high resolution stages, and a 94.6% faster loss reduction compared to conventional methods.