• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1951-1956
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• 2003

It is known that HIV (Human Immunodeficiency Virus) infection, which causes AIDS after some latent period, is a dynamic process that can be modeled mathematically. Effects of available anti-viral drugs, which prevent HIV from infecting healthy cells, can also be included in the model. In this paper we illustrate control theory can be applied to a model of HIV infection. In particular, the drug dose is regarded as control input and the goal is to excite an immune response so that the symptom of infected patient should not be developed into AIDS. Finite horizon optimal control is employed to obtain the optimal schedule of drug dose since the model is highly nonlinear and we want maximum performance for enhancing the immune response. From the simulation studies, we find that gradual reduction of drug dose is important for the optimality. We also demonstrate the obtained open-loop optimal control is vulnerable to parameter variation of the model and measurement noise. To overcome this difficulty, we finally present nonlinear receding horizon control to incorporate feedback in the drug treatment.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.1
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• pp.304-320
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• 1996

A multiple production .epsilon. equation model was developed in the low Reynolds number $\kappa$-$\varepsilon$ model with the aids of DNS data. We derived the model theoretically and avoided the use of empirical correlations as much as possible in order for the model to have generality in the prediction of complex turbulent flow. Unavoidable model constants were, however, optimized with the aids of DNS data. All the production and dissipation models in the $\varepsilon$ equation were modified with damping functions to satisfy the wall limiting behavior. A new $f_{\mu}$ function, turbulent diffusion and pressure diffusion model for the k and .epsilon. equations were also proposed to satisfy the wall limiting behavior. By, computational investigation on the plane channel flows, we found that the multiple production model for .epsilon. equation could improve the near wall turbulence behavior compared with the standard production model without the complicated empirical modification. Satisfication of the wall limiting conditions for each turbulence model term was found to be most important for the accurate prediction of near wall turbulence behaviors.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• The Journal of Industrial Distribution & Business
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• v.10 no.12
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• pp.7-14
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• 2019

Purpose: In Korea, win-win growth policy has been successfully implemented in supply chain and logistics management. In the policy, it is recommended to support supply chain partners with various mechanisms including financial and technical aids. This study attempts to scientifically analyze the effects of direct and indirect win-win growth policy factors on supply chain and logistics management performance through partnership factors. Research design, data and methodology: This study builds a structural equation model reflecting the relationship between the win-win growth policy, partnership and performance factors. The proposed model is verified with the PLS (Partial Least Squares regression) methodology. Data from shipper and logistics companies were collected and analyzed by the PLS model. Results: The analysis showed that both direct and indirect policy factors are meaningful to improve supply chain and logistics performance. Indirect support factors including R&D, management innovation, human resources development and educational supports have positive impacts on partnership factors. Direct support factors including financial aids and fairness also have positive impacts on the performance. Conclusions: This study is meaningful in that it suggests a turning point in which supply chain Win-win growth and partnership efforts are perceived as new value-creating mechanism rather than unilateral cost reduction for logistics industry.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.198-205
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• 2011

GPS, ARPA, AIS, NAVTEX, VHF as modern aids-to-navigation equipments improve the safe navigation and help to reach a reduction in marine accidents by providing images, numeric values, texts, audio-based information for mates, However, we also noticed that it's complicate and difficult for a mate to acquire and analyze such information from these devices while he should devote himself to bridge watchkeeping especially in the urgent situation. Language is another way to get information and free the eyes and hands, so, to solve the problem above, we are trying to propose a new aids-to-navigation system, which can understand and merge multimedia marine safety information, analyze the situation and provide the necessary information in language. In this paper, we try to suggest a meaning interpretation model for supporting linguistic navigation safety information.

• Journal of Korean Academy of Nursing Administration
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• v.20 no.1
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• pp.95-105
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• 2014

Purpose: The purpose of this study was to examine trends in number of nursing staff and skill mix. Methods: Nursing staff and skill mix were measured using the number of nursing staff including nurse aids and registered nurses per bed. Descriptive and panel data regression analyses were conducted using data on long-term care hospitals which included yearly series data from 2006 to 2010 for 119 hospitals. Results: The number of nursing staff per bed increased significantly but percentage of registered nurses decreased significantly from 2007 to 2010. The regression model explained this variation as much as 34.9% and 43.8%. Conclusion: The results showed that in long-term care hospitals there were more nurse aids employed instead of registered nurses after the implemention of differentiated inpatient nursing fees. Thus clarifying the job descriptions for nurses and nurse aids is needed and appropriate hospital incentive policies should be implemented.

• Journal of muscle and joint health
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• v.22 no.1
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• pp.20-29
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• 2015

Purpose: The study was undertaken to investigate effects of susceptibility to musculoskeletal disorder, social support, and environmental aids on exercise adherence intention and to identify factors contributing to exercise adherence intention among university students. Methods: The study was a descriptive study with 277 students from 3 universities. Data were collected from March 5 to May 30, 2014 using a structured self-report questionnaire. Data were analyzed using descriptive statistics, t-test, one-way ANOVA, Pearson correlation coefficients, and Hierarchical multiple regression. Results: The explanatory power of the predictive model involving the demographic factors, susceptibility to musculoskeletal disorder, social support, and environmental aids was 29%, and the subjects' gender, health concern, experience of musculoskeletal injury, regular exercise, and social support were identified as main factors having influence. Conclusion: The results of this study will be helpful in understanding the importance of environmental factors for increasing physical activities and will be used as basic data for development of exercise programs to increase exercise adherence intention for their continuous exercise.

• Korean Management Science Review
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• v.11 no.2
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• pp.185-206
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• 1994

This paper investigated, using a flexible approach, the effects of the psychological type of the decision maker and the advanced format of information presentation on decision maker performance in a computer-simulated production game. The current sutdy was guided by a model derived from a general model developed by Chervany, Dickson, and Kozar(1972). The experimental model had two dependent variables; total profit and decision making time. Three independent variables representing the psychological type of the decision maker, the report format, and decision aids were used in this study.