• Journal of Environmental Policy
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• v.6 no.3
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• pp.91-114
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• 2007

The cooperative cost sharing scheme for Dust and Sand Storm(DSS) in North East Asia, as suggested in Song and Nagaki(2007), may not be feasible due to possible defection(s) of participating countries. If non-cooperative strategies are more plausible, Nash equilibrium can suggest possible outcomes of the cost sharing game. The result from the continuous strategy model shows that there exists an infinite number of Nash equilibrium such that the summation of investment from each country is always equal to the required budget of the ADS pilot project. It is also discussed that the discrete strategy model points to only 3 Nash equilibria in continuous strategy game outcome and the cooperative game solution may be just one of the infinite equilibria.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2038-2057
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• 2017

Gaussian learning is a new technology in the computational intelligence area. However, this technology weakens the learning ability of a particle swarm and achieves a lack of diversity. Thus, this paper proposes a vector Gaussian learning strategy and presents an effective approach, named particle swarm optimization based on vector Gaussian learning. The experiments show that the algorithm is more close to the optimal solution and the better search efficiency after we use vector Gaussian learning strategy. The strategy adopts vector Gaussian learning to generate the Gaussian solution of a swarm's optimal location, increases the learning ability of the swarm's optimal location, and maintains the diversity of the swarm. The method divides the states into normal and premature states by analyzing the state threshold of the swarm. If the swarm is in the premature category, the algorithm adopts an inertia weight strategy that decreases linearly in addition to vector Gaussian learning; otherwise, it uses a fixed inertia weight strategy. Experiments are conducted on eight well-known benchmark functions to verify the performance of the new approach. The results demonstrate promising performance of the new method in terms of convergence velocity and precision, with an improved ability to escape from a local optimum.

• 대한공업교육학회지
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• v.31 no.1
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• pp.23-45
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• 2006

The purpose of this study is to develop a instructive strategy model of cooperative learning for practical class in technical high school. To achieve this purpose, this study has conducted related literature investigation and interviewed with professionals for reconstruction of practice contents. As a result, 15 steps instructional strategy model of cooperative learning was designed and this model based on traditional 4 steps model, Jigsaw and STAD model which have been verified as effect. To complete the final project, all the team members must cooperate themselves and tutor their peers with learning guides which are constructed as a modular system. This instructional strategy model which is correlated with modular instruction, peer tutoring and cooperative learning is expected to enhance students' school work of psychomotor domain as well as cognitive domain and affective domain.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.127-130
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• 1998

In this paper, we propose a method of cooperative control(T-cell modeling) and selection of group behavior strategy(B-cell modeling) based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-call respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based of clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.3
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• pp.253-270
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• 2015

Two major simultaneous attack strategies have been introduced, as one of cooperative attack of multiple missiles. One strategy is an undesignated time attack, in which the missiles communicate among themselves to synchronize the arrival times by reducing the mutual differences of times-to-go of multiple missiles during the homing. The other is a designated time attack, in which a common impact time is commanded to all members in advance, and thereafter each missile tries to home on the target on time independently. For this individual homing, Impact-Time-Control Guidance (ITCG) law is required. After introducing cooperative proportional navigation (CPN) for the first strategy, this article presents a new closed-form ITCG guidance solution for the second strategy. It is based on the linear formulation, employing base trajectories driven by PNG with various navigation constants. Nonlinear simulation of several engagement situations demonstrates the performance and feasibility of the proposed ITCG law.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.9
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• pp.542-549
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• 2003

In this paper, a novel approach to generator maintenance scheduling strategy in competitive electricity markets based on non-cooperative dynamic game theory is presented. The main contribution of this study can be considered to develop a game-theoretic framework for analyzing strategic behaviors of generating companies (Gencos) from the standpoints of the generator maintenance-scheduling problem (GMP) game. To obtain the equilibrium solution for the GMP game, the GMP problem is formulated as a dynamic non-cooperative game with complete information. In the proposed game, the players correspond to the profit-maximizing individual Gencos, and the payoff of each player is defined as the profits from the energy market. The optimal maintenance schedule is defined by subgame perfect equilibrium of the game. Numerical results for two-Genco system by both proposed method and conventional one are used to demonstrate that 1) the proposed framework can be successfully applied in analyzing the strategic behaviors of each Genco in changed markets and 2) both methods show considerably different results in terms of market stability or system reliability. The result indicates that generator maintenance scheduling strategy is one of the crucial strategic decision-makings whereby Gencos can maximize their profits in a competitive market environment.

• Journal of Science Education
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• v.35 no.1
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• pp.91-101
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• 2011

In this study, Jigsaw III cooperative learning strategy and traditional learning strategy have been applied to the 'electricity' chapter of grade 8 science textbooks to know the effects of learning strategy, gender, and GPA on the students' science achievement and science learning attitude of middle school female students in gender-separated classes. For this purpose, 143 students of 4 classes in separated classes were chosen from a middle school in Daegu. One female class and one male class were assigned to the experimental group and other female class and male class were assigned to the control group. Traditional learning strategy was applied to the control group and the Jigsaw III cooperative learning strategy was applied to the experimental group. Four worksheets for expert groups were used for 18 hours through 5 weeks. Both tests for science achievement and learning attitude were administered as pre and post test. The test results were analyzed through analysis of covariance(ANCOVA) as pre test score as covariant The overall conclusions of this study were as follows: The Jigsaw III cooperative learning has improved science achievement, especially on subjective-type questions, of female students and mid-lower level students. The Jigsaw III Cooperative Learning has also improved self-directed attitude toward science learning. Female students have expressed more positive opinion about the Jigsaw III cooperative learning.

• The Mathematical Education
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• v.48 no.3
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• pp.329-352
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• 2009

The purpose of this study was to investigate the effects of small group cooperative communicative activities on the strategies for estimating measurement. To do this, two research questions were set as follow: First, are there any differences between strategies employed by students in the experimental group and the control group before and after the estimating measurement activities? Second, are there any differences between strategies employed by students in different ability levels(upper, middle, lower) of pre-estimating measurement test in the experimental group? The research results were drawn from the investigation as below: First, the strategical change of before and after the estimating measurement tasks in the experimental group was quite noticeable. Unlike the small strategical change in the control group, small group cooperative communicative learning resulted in a decrease of simple memorization and guessing strategies and an increase of refined strategies such as the standard strategy, clustering, unit load and so on. Second, mathematical communicative activities in a small group cooperative learning showed that the students in the upper level of pre-estimating measurement test used more refined strategies and the students in the lower level used simple memorization and guessing strategy more frequently. And through interaction in small group, students could have chances to recognize error of strategies and to modify and learn strategies. In conclusion, small group cooperative activities allowed students to have chances to communicate mathematically and it is a efficient way of helping students learn estimating measurement strategies.

• Journal of The Korean Association For Science Education
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• v.20 no.4
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• pp.611-623
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• 2000

The cooperative learning movement began as parts of the desegregation process in America, aiming at increasing academic achievement and social skills among diverse students. Cooperative learning may be defined as a classroom learning environment in which students work together in small heterogeneous groups. Although many studies have shown the effectiveness of cooperative learning in a variety of subjects, relatively few have focused on biology. In this study, we investigated the effects of cooperative learning on students' achievement and attitude of middle school biology students. For this purpose this study compared three sections. In one section, a cooperative learning strategy was used. Second section was taught in small groups and the third section was instructed in the traditional method. The unit 'Structures and functions of animals' was used. A total of 188 students were included in this study. These classes were treated for 10hours during 10weeks from September 1 to November 28, 1999. The pretests-posttests control group design was applyed. An analysis of covariance(ANCOVA) was used as the data analysis procedure. Significant differences were found in the achievement and the attitude of students using cooperative learning strategy(p<.05) when compared to traditional classroom structure and small group learning. Cooperative learning was more effective in the low-ability and average-ability students than the high-ability students in the science achievement. Cooperative learning is effective in both male and female students. And students in the cooperative group achieved better than those in other groups in affective, behavioral, and intention-cognitive domain of science attitude.

• Journal of The Korean Association For Science Education
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• v.20 no.4
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• pp.519-526
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• 2000

In this study, the effects of visual organization and cooperative learning in problem-solving strategy were investigated. Three classes (N=127) at a high school were assigned to SV (Strategy-Visual organization) group, SVC (Strategy-Visual organization-Cooperative learning) group, and control group. After instructions, students' multiple-choice problem-solving ability, strategy performing ability, anxiety about chemistry learning, perception of involvement, and motivation to learning science were examined. Although multiple-choice problem-solving ability was not different significantly, there was a significant main effect in strategy performing ability. The scores of the SV and SVC groups were significantly higher than those of the control group, especially in the subcategories of problem understanding and recalling related principles. In the tests of perception of involvement and motivation to learning science, the scores of the SV and SVC groups were also significantly higher than those of the control group. However, problem-solving strategy using visual organization could not alleviate anxiety about chemistry learning.