• Cross-Cultural Studies
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• v.30
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• pp.259-277
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• 2013

This article covers realization of tone in Modern Chinese by the leverage principle, and then explores its teaching strategies. The results of this study are as follows: The teaching strategies are as follows: Firstly, pronouncing Chinese vowels always takes far longer than you anticipate. Secondly, pronounce and practice Chinese vowels with leverage principle. Thirdly, understand and practice the sound change rule of '?'.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.160-161
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• 2012

The traditional theory regarding the pivot point of a ship during maneuvering, so called apparent pivot point, is located nearly at 1/3 ship's length from the bow when the ship is moving ahead, and between 1/4 ship's length from the stern and the rudder post when going astern. The pivot point is sometimes considered to be the centre of leverage for forces acting on the ship. However, the pivot point is located out of ship due to strong lateral force, such as current and it is very inconvenient to use during maneuvering a ship. In this paper firstly, pivot points due to ship's condition are investigated carefully. And then the center of lateral resistance used at the present are determined. While a new lateral force is added, we can compare the pivot point with the center of lateral forces. Finally, we will suggest the center of all lateral forces for maneuvering instead of pivot point. Especially, it will be very helpful for pilots to handle ships in simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.4
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• pp.474-484
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• 2024

Reinforcement learning, which are also studied in the field of defense, face the problem of sample efficiency, which requires a large amount of data to train. Transfer learning has been introduced to address this problem, but its effectiveness is sometimes marginal because the model does not effectively leverage prior knowledge. In this study, we propose a stochastic initial state randomization(SISR) method to enable robust knowledge transfer that promote generalized and sufficient knowledge transfer. We developed a simulation environment involving a cooperative robot transportation task. Experimental results show that successful tasks are achieved when SISR is applied, while tasks fail when SISR is not applied. We also analyzed how the amount of state information collected by the agents changes with the application of SISR.

• Journal of Industrial Convergence
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• v.12 no.2
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• pp.54-62
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• 2014

The significance of the research is to leverage on the policy makers and school education, and research in terms of human rights issues and for the improvement of multicultural education by seeking an effective training plan with the purpose of the present study it. The efforts to address human rights issues through real multicultural care center starts with the question of human rights education in multicultural education methodology that can protect the human rights of migrant workers, immigrant youth in a multicultural society such situation in Korea by. Accordingly we suggest that it is appropriate to human rights education in the moral multicultural care center for human rights education. Cant because the regular students on the basis of morality that respects the human rights of migrant workers, immigrant adolescents 'human rights' training done 'pursue human rights' migrant worker, immigrant youth in their own rights, as well as multicultural education is through morality The Seen to suggest ways through the development of multicultural education issues and the results of these studies.

• Journal of Gastric Cancer
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• v.23 no.3
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• pp.388-399
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• 2023

Gastric cancer remains a significant global health concern, coercing the need for advancements in imaging techniques for ensuring accurate diagnosis and effective treatment planning. Artificial intelligence (AI) has emerged as a potent tool for gastric-cancer imaging, particularly for diagnostic imaging and body morphometry. This review article offers a comprehensive overview of the recent developments and applications of AI in gastric cancer imaging. We investigated the role of AI imaging in gastric cancer diagnosis and staging, showcasing its potential to enhance the accuracy and efficiency of these crucial aspects of patient management. Additionally, we explored the application of AI body morphometry specifically for assessing the clinical impact of gastrectomy. This aspect of AI utilization holds significant promise for understanding postoperative changes and optimizing patient outcomes. Furthermore, we examine the current state of AI techniques for the prognosis of patients with gastric cancer. These prognostic models leverage AI algorithms to predict long-term survival outcomes and assist clinicians in making informed treatment decisions. However, the implementation of AI techniques for gastric cancer imaging has several limitations. As AI continues to evolve, we hope to witness the translation of cutting-edge technologies into routine clinical practice, ultimately improving patient care and outcomes in the fight against gastric cancer.

• IMMUNE NETWORK
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• v.14 no.2
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• pp.73-80
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• 2014

Because autoimmune diseases (AIDs) result from a complex combination of genetic and epigenetic factors, as well as an altered immune response to endogenous or exogenous antigens, systems biology approaches have been widely applied. The use of multi-omics approaches, including blood transcriptomics, genomics, epigenetics, proteomics, and metabolomics, not only allow for the discovery of a number of biomarkers but also will provide new directions for further translational AIDs applications. Systems biology approaches rely on high-throughput techniques with data analysis platforms that leverage the assessment of genes, proteins, metabolites, and network analysis of complex biologic or pathways implicated in specific AID conditions. To facilitate the discovery of validated and qualified biomarkers, better-coordinated multi-omics approaches and standardized translational research, in combination with the skills of biologists, clinicians, engineers, and bioinformaticians, are required.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.540-542
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• 2023

Due to the serious issues posed by facial manipulation technologies, many researchers are becoming increasingly interested in the identification of face forgeries. The majority of existing face forgery detection methods leverage powerful data adaptation ability of neural network to derive distinguishing traits. These deep learning-based detection methods frequently treat the detection of fake faces as a binary classification problem and employ softmax loss to track CNN network training. However, acquired traits observed by softmax loss are insufficient for discriminating. To get over these limitations, in this study, we introduce a novel discriminative feature learning based on Vision Transformer architecture. Additionally, a separation-center loss is created to simply compress intra-class variation of original faces while enhancing inter-class differences in the embedding space.

• Research in Mathematical Education
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• v.25 no.3
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• pp.201-225
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• 2022

This paper details case study vignettes that focus on enhancing the teaching and learning of geometry and measurement in the elementary grades with attention to pedagogical practices for teaching through problem solving with rigor and centering equitable teaching practices. Rigor is a matter of equity and opportunity (Dana Center, 2019). Rigor matters for each and every student and yet research indicates historically disadvantaged and underserved groups have more of an opportunity gap when it comes to rigorous mathematics instruction (NCTM, 2020). Along with providing a conceptual framework that focuses on the importance of equitable instruction, our study unpacks ways teachers can leverage their deep understanding of geometry and measurement learning trajectories to amplify the mathematics through rigorous problems using multiple approaches including learning by doing, challenged-based and mathematical modeling instruction. Through these vignettes, we provide examples of tasks taught through rigorous problem solving approaches that support conceptual teaching and learning of geometry and measurement. Specifically, each of the three vignettes presented includes a task that was implemented in an elementary classroom and a vertically articulated task that engaged teachers in a professional learning workshop. By beginning with elementary tasks to more sophisticated concepts in higher grades, we demonstrate how vertically articulating a deeper understanding of the learning trajectory in geometric thinking can add to the rigor of the mathematics.

• Journal of muscle and joint health
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• v.31 no.2
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• pp.95-106
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• 2024

Purpose: This study investigated how distress and stigma affect the quality of life (QOL) in stroke patients. Methods: A descriptive research design was utilized with 150 stroke patients from three general and three long-term care facilities. Data were collected through an 86-item questionnaire from February 15 to April 10, 2023, using measures of distress, stigma, and QOL. Analysis was conducted using descriptive statistics, independent t-tests, one-way ANOVA, Pearson's correlation coefficients, and hierarchical regression analysis in SPSS/WIN 25.0. Results: The average QOL score was 156.37±38.27 out of 245 points. Factors affecting QOL of stroke patients were distress (β=-.56, p<.001), stigma(β=-.26, p<.001), biplegia (β=-.11, p=.045), and unemployment (β=-.10, p=.045), explaining 68% of the QOL variance. Conclusion: Programs aimed at reducing distress and stigma in stroke patients are essential for enhancing QOL. Effective strategies should address post-stroke physical and mental states, prevent complications, restore health, reduce anxiety, and leverage family and social support to mitigate stigma. Special attention is needed for stroke patients with hemiplegia and those who are unemployed.

• Journal of Industrial Convergence
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• v.15 no.2
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• pp.37-43
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• 2017

As the number of SSM(Super Supermarket) has been growing, the conflict between large companies and small-to-medium retailers is being deeper in which large-sized market has been growing rapidly and small to medium retailers has been depressed. To solve the conflict, the government enacted the system of business limiting of large enterprises by SMEs. It brought growth of sales of small-to-medium retailers. However, unintended effects were caused by the system. This research aims to analyze underlying structure beyond conflicts between SSM and small to medium retailers using system thinking and draw relationships between key factors. Thus we can provide political alternatives through simulation model which is developed based on the factors.