• Journal of Agricultural Extension & Community Development
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• v.12 no.2
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• pp.137-150
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• 2005

Although the rate of women farmer's participation in agricultural activities have been increased upto 52.7 % as of year 2003, Korean society has not fully recognized their roles in rural society. According to the agricultural basic law, most of rural women were engaged in agriculture as full time job, however, only about 11% of them could have supporting evidence of themselves as farmer having legal right. If women farmers faced some unexpected things such as a traffic accident, insurance company would not reward them as farmers unless they provide written proof of their job as farm worker or farm owner. Based on lawyer's legal advice, the authors developed a diary called "Saenghwalilji", a daily diary based on their time use and bookkeeping to prove the fact of their contribution to income generation of the farm. After examination of the diary, 18 persons out of 29 volunteers kept two types of dairy for the period of two weeks, and they reported it was very useful. Finally the better one of two was selected after reflecting the suggestions from the respondents. The "Saenghwalilji", will be very useful proof of women farmer's contribution to income, at the same time improving their farm management through better use of daily life time.

• Research in Community and Public Health Nursing
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• v.15 no.3
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• pp.471-482
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• 2004

Purpose: This study intended to identify personality factors and related problematic behaviors of adolescents who drink alcohol in order to provide basic data for developing nursing programs. Methods: The data were collected from October to December 2002 from 1.080 high school students in Seoul. The Revised Cloninger's Tri-dimensional Personality Questionnaire (TPQ) was used to measure their personalities. The alcohol expectancy was measured using the tool revised by Cho (1999) and stress levels were measure using a stress tool revised Cho (1998). The data were analyzed with SPSS Windows using Chi square test. independent t-test. and logistic regression analysis. Results: 1. The percentage of fathers who drank was 79.8%. mothers. 54.3%. and friends. 54.3%. The alcohol expectancy averaged 6.36 while the stress levels were 132.79. 2. It was found that there are significant differences (p<.001) in problematic drinking behaviors according to the following variables: second year high school students among all grade variables, more monthly pocket money for the amount of money variables, the group of students who smoked in the case of the variable related to smoking, spending more time using the Internet for the Internet use variable, and having friends who drink 65.6% for the friend variable. The alcohol expectancy scale of those students who showed problematic drinking behaviors was higher than that of those who did not. There are four family-related stress subscales, and there was a significant difference among them (p<.05). Among the personal characteristics, the group who displayed problematic drinking behaviors seeks new experiences and reward dependence more than the group who did not exhibit those behaviors, and there were significant differences between the two groups (p<.001). 3. When the socio-demographic and drinking-related factors were controlled, the tendency of seeking new experiences increased the risk of problematic behaviors 1.07 times (p<.05). Compared to the non smoking group, the smoking group was found to have a 5.06 time (p<.001) greater risk of displaying problematic drinking behaviors. In comparison with the non drinking group, the drinking group was also found to have a 5.31 time (p<.001) greater risk of exhibiting problematic drinking behaviors. The group with high alcohol expectancy scores was significantly different from the group with the no alcohol expectancy, showing a 1.26 time (p<.00l) greater risk of problematic drinking behaviors. Conclusions: Based on these results, the problematic drinking behaviors were connected with alcohol expectancies, friends and personality types. Therefore, we should develop an alcoholic prevention program for adolescence considering the above results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1036-1057
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• 2013

Wireless body area network (WBAN) is a promising candidate for future health monitoring system. Nevertheless, the path to mature solutions is still facing a lot of challenges that need to be overcome. Energy efficient scheduling is one of these challenges given the scarcity of available energy of biosensors and the lack of portability. Therefore, researchers from academia, industry and health sectors are working together to realize practical solutions for these challenges. The main difficulty in WBAN is the uncertainty in the state of the monitored system. Intelligent learning approaches such as a Markov Decision Process (MDP) were proposed to tackle this issue. A Markov Decision Process (MDP) is a form of Markov Chain in which the transition matrix depends on the action taken by the decision maker (agent) at each time step. The agent receives a reward, which depends on the action and the state. The goal is to find a function, called a policy, which specifies which action to take in each state, so as to maximize some utility functions (e.g., the mean or expected discounted sum) of the sequence of rewards. A partially Observable Markov Decision Processes (POMDP) is a generalization of Markov decision processes that allows for the incomplete information regarding the state of the system. In this case, the state is not visible to the agent. This has many applications in operations research and artificial intelligence. Due to incomplete knowledge of the system, this uncertainty makes formulating and solving POMDP models mathematically complex and computationally expensive. Limited progress has been made in terms of applying POMPD to real applications. In this paper, we surveyed the existing methods and algorithms for solving POMDP in the general domain and in particular in Wireless body area network (WBAN). In addition, the papers discussed recent real implementation of POMDP on practical problems of WBAN. We believe that this work will provide valuable insights for the newcomers who would like to pursue related research in the domain of WBAN.

• Journal of the Korea Society for Simulation
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• v.29 no.1
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• pp.39-46
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• 2020

The utilization of artificial intelligence (AI) in the engagement has been a key research topic in the defense field during the last decade. To pursue this utilization, it is imperative to acquire a realistic simulation to train an AI engagement agent with a synthetic, but realistic field. This paper is a case study of training an AI agent to operate with a hardware realism in the air-warfare dog-fighting. Particularly, this paper models the pursuit of an opponent in the dog-fighting setting with a gun-only engagement. In this context, the AI agent requires to make a decision on the pursuit style and intensity. We developed a realistic hardware simulator and trained the agent with a reinforcement learning. Our training shows a success resulting in a lead pursuit with a decreased engagement time and a high reward.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.297-305
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• 2017

As the development of autonomous vehicles becomes realistic, many automobile manufacturers and components producers aim to develop 'completely autonomous driving'. ADAS (Advanced Driver Assistance Systems) which has been applied in automobile recently, supports the driver in controlling lane maintenance, speed and direction in a single lane based on limited road environment. Although technologies of obstacles avoidance on the obstacle environment have been developed, they concentrates on simple obstacle avoidances, not considering the control of the actual vehicle in the real situation which makes drivers feel unsafe from the sudden change of the wheel and the speed of the vehicle. In order to develop the 'completely autonomous driving' automobile which perceives the surrounding environment by itself and operates, ability of the vehicle should be enhanced in a way human driver does. In this sense, this paper intends to establish a strategy with which autonomous vehicles behave human-friendly based on vehicle dynamics through the reinforcement learning that is based on Q-learning, a type of machine learning. The obstacle avoidance reinforcement learning proceeded in 5 simulations. The reward rule has been set in the experiment so that the car can learn by itself with recurring events, allowing the experiment to have the similar environment to the one when humans drive. Driving Simulator has been used to verify results of the reinforcement learning. The ultimate goal of this study is to enable autonomous vehicles avoid obstacles in a human-friendly way when obstacles appear in their sight, using controlling methods that have previously been learned in various conditions through the reinforcement learning.

• Smart Media Journal
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• v.6 no.4
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• pp.94-100
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• 2017

Procurement of development funds is a very difficult process in the Korean game industry where competition is fierce. Recently, crowdfunding has been used as a convenient platform to attract potential investors to secure the development cost of the game. This study explored the factors influencing the success of crowdfunding for game development projects. We collected data on 229 game development projects in Tumblebuck, a reward-based crowdfunding site in Korea. According to the results of the logistic regression model, the factors that have a positive effect on the success of funding are the average compensation amount relative to the target amount, the number of SNS shares, the number of updates, and the originality of the proposed game. Video playback time has been found to have a negative impact. Based on the results of this study, it is expected that planning a game development project considering the variables affecting the success of crowdfunding will help financing.

• The Korean Journal of Food And Nutrition
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• v.22 no.2
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• pp.166-176
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• 2009

This study was performed to develop dietary education programs for children, by researching the actual conditions of dietary education and its demand aimed at teachers in child centers in Masan. Most of the interviewed teachers were in their 20s(71%) with under 5 years teaching experiences(56.8%), and working in a kindergarten environment(34.9%). The rate of doing dietary education on mealtime was 96.4%. The main items taught pertained to 'not leaving food(20.6%)' and 'washing hands before meals(20.5%)'. The primary teaching method for students with unbalanced eating habits was 'eating after teaching them to understood(76.8%). The primary reward for good behavior was 'using food(76.8%)', usually as 'candy'(50.8%) or 'cookies'(25.8%). The desirable dietary education type was 'during spare moments(52.6%)' and 'at mealtime (23.5%)'. The concepts taught were 'balanced eating(23.2%)' and 'food hygiene(21.2%), and the students were interested in 'the roles of foods and nutrients'(34.5%), 'balanced eating(20.9%)', and 'food hygiene(19.1%)'. Educational activities encompassed 'pictures and drawing(25.7%)', 'fairy tales(23.4%)', 'songs(19.4%)', and 'play(14.1%)'. Also, the activities of most interest were 'fairy tales(29.4%)', 'play(24.4%)', and then 'songs(23.1%)'. The greatest difficulties during dietary education were 'attracting interest from the children(37.8%)' and 'making and purchasing materials(33.9%)'. Approximately, 44.2% of the teachers had experiences in dietary education, and 96.4% stated teachers had the intention to participate in dietary education. They want to address 'child meal direction(23.0%)', 'health problems(22.7%)', and then 'child nutrient requirements (17.3%)'. Also the majority wanted it two times per year(57.6%) or one time per year(30.9%). This study indicated that proper dietary education must be established in child centers by developing various practical dietary education programs and then implementing them.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.21 no.3
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• pp.146-155
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• 2011

Objectives: This study was conducted to investigate the association between job stress and mental health among male and female workers in a large electric manufacture company. Methods: A cross-sectional study was carried out on 3,228 employees who participated in annual medical check-up working in a large electric manufacture company in Gyeonggi Province. Medical check-up and self-administrated questionnaire were performed at the same time. Korean Occupational Stress Scale Short Form (KOSS-SF) and Psychosocial Wellbeing Index Short Form (PWI-SF) were applied to assess occupational stress and mental health. Hierarchical multiple linear regression and multiple logistic regression were performed to estimate the association between job stress and mental health. Results: The proportion of high risk of mental health was 17.1% in male, and 46.9% in women. Job stress had a greater effect on mental health than other general and work characteristics. All subscales of job stress were revealed to affect mental health. Bad occupational climate and lack of reward are the strongest risk factors in mental health of male and female respectively. Conclusions: Our results suggest that job stress could affect mental health among large electronic manufacture workers.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.65-70
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• 2001

We consider a hyper-redundant system that consists of many uniform units. The hyper-redundant system has many degrees of freedom and it can accomplish various tasks. Applysing the reinforcement learning to the hyper-redundant system is very attractive because it is possible to acquire various behaviors for various tasks automatically. In this paper we present a new reinforcement learning algorithm "Q-learning with propagation of motion". The algorithm is designed for the multi-agent systems that have strong connections. The proposed algorithm needs only one small Q-table even for a large scale system. So using the proposed algorithm, it is possible for the hyper-redundant system to learn the effective behavior. In this algorithm, only one leader agent learns the own behavior using its local information and the motion of the leader is propagated to another agents with time delay. The reward of the leader agent is given by using the whole system information. And the effective behavior of the leader is learned and the effective behavior of the system is acquired. We apply the proposed algorithm to a snake-like hyper-redundant robot. The necessary condition of the system to be Markov decision process is discussed. And the computer simulation of learning the locomotion is demonstrated. From the simulation results we find that the task of the locomotion of the robot to the desired point is learned and the winding motion is acquired. We can conclude that our proposed system and our analysis of the condition, that the system is Markov decision process, is valid.

• Journal of Korea Game Society
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• v.11 no.4
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• pp.37-48
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• 2011

As people increasingly play online games, numerous new features have been proposed to increase players' log-on time at online gaming sites. However, few studies have investigated why people continue to play certain online games. This research would verify that enjoyment experience could be explained by the conceptual framework. In the first, this study results indicate that customers would show a higher level of loyalty if they had an optimal experience with the games. The state of flow was felt when players were aware of opportunities for personal interaction and social interaction. The personal interaction could be motivated either to achieve the high cognitive performance or by providing the equity of distribution of the objective performance in order to examine players' cognitive performance; the social interaction can be motivated either to enhance a high level of self-esteem of player or to achieve the positive reputation in order to evaluate their self-esteem. This finding can answer the questions of what enjoyment experience is and why players are repeatedly playing specific online games.