• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.5 s.248
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• pp.585-594
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• 2006

The joined-wing is a new concept of the airplane wing. The fore-wing and the aft-wing are joined together in a joined-wing. The range and loiter are longer than those of a conventional wing. The joined-wing can lead to increased aerodynamic performance and reduction of the structural weight. In this research, dynamic response optimization of a joined-wing is carried out by using equivalent static loads. Equivalent static loads are made to generate the same displacement field as the one from dynamic loads at each time step of dynamic analysis. The gust loads are considered as critical loading conditions and they dynamically act on the structure of the aircraft. It is difficult to identify the exact gust load profile. Therefore, the dynamic loads are assumed to be (1-cosine) function. Static response optimization is performed for the two cases. One uses the same design variable definition as dynamic response optimization. The other uses the thicknesses of all elements as design variables. The results are compared.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.99-106
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• 2004

This paper presents some comparisons between Cournot-Nash and Stackelberg game in bi-level program, composed of both upper level program and lower level one. The upper level can be formulated to optimize a specific objective function, while the lower formulated to express travelers' behavior patterns corresponding to the design parameter of upper level problem. This kind of hi-level program is to determine a design parameter, which leads the road network to an optimal state. Bi-level program includes traffic signal control, traffic information provision, congestion charge and new transportation mode introduction as well as road expansion. From the view point of game theory, many existing algorithms for bi-level program such as IOA (Iterative Optimization Assignment) or IEA (Iterative Estimation Assignment) belong to Cournot-Nash game. But sensitivity-based algorithms belongs to Stackelberg one because they consider the reaction of the lower level program. These two game models would be compared by using an example network and show some results that there is no superiority between the models in deterministic case, but in stochastic case Stackelberg approach is better than that of Cournot-Nash one as we expect.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.61-66
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• 2024

This paper aims to design a simulation for path-finding of objects in a simulation or game environment using reinforcement learning techniques. The main feature of this study is that the objects in the simulation are trained to avoid obstacles at random locations generated on a given track and to automatically explore path to get items. To implement the simulation, ML Agents provided by Unity Game Engine were used, and a learning policy based on PPO (Proximal Policy Optimization) was established to form a reinforcement learning environment. Through the reinforcement learning-based simulation designed in this study, we were able to confirm that the object moves on the track by avoiding obstacles and exploring path to acquire items as it learns, by analyzing the simulation results and learning result graph.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.140-150
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• 2009

Difference of individual character is defined Cerebral Hemispheric Model(CHM) to develop individual intellectual abilities in this paper. Component of preferred online-game is surveyed in accordance with individual character, and investigated for possible applications. An individual is classified with 2 modes of CHM that take charge of intellectual abilities; abilities is character, taste, personality decision-making and behavior patterns; that is closely related to creativity. Difference of game component could be investigated with correlation table of cerebral preference patterns (CPP) that was drawn up with survey. Individual brain preferences (IBP) became clear through preference of individual in the investigation, and suggested concept guide-line to develop other brain preferences. Thus, this study is able to realize from education game to a great variety of contents that base on the development of thinking-faculties as optimization of user preference, can be the basic data of self-development, to improve intellectual faculties as development of individual thinking preference.

• Journal of Korea Game Society
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• v.7 no.4
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• pp.93-104
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• 2007

In the complex real-time multi-agent system such as game environment, dynamic task allocations are repeatedly performed to achieve a goal in terms of system efficiency. In this research, we present a task allocation scheme suitable for the real-time multi-agent environment. The scheme is to optimize the task allocation by complementing existing coordination agent with $A^*$ algorithm. The coordination agent creates a status graph that consists of nodes which represent the combinations of tasks and agents, and refines the graph to remove nodes of non-execution tasks and agents. The coordination agent performs the selective utilization of the $A^*$ algorithm method and the greedy method for real-time re-allocation. Then it finds some paths of the minimum cost as optimized results by using $A^*$ algorithm. Our experiments show that the coordination agent with $A^*$ algorithm improves a task allocation efficiency about 25% highly than the coordination agent only with greedy algorithm.

• Cartoon and Animation Studies
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• s.14
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• pp.151-164
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• 2008

Cross platform game has brought about the expansion of game market, which results in technology innovation overcoming the limit of game consumption. The new model integrates both off and online game services. Gamers can now enjoy game service regardless of age, time, and space. If the technology evolution model of digital contents like cross-platform game engine can provide contents for several platform at the same time, the interactive service can be utilized into maximum level. It is also necessary to allocate, switch data as well as to innovate the transmission technology of data according to each platform. Providing the same contents for several platform as many as possible can be the most suitable strategy to enhance the efficiency and profits. However if the interactive service can be accomplished completely, the development of data switching technology and distribution should be made. To be a leader in the next digital contents market, one should develop the network engine technology which can embody the optimization of consumption in the interactive network service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5759-5779
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• 2017

As the main means to cope with the stubborn problem of drunk driving, the inspection of drunk driving has already been paid more attention and thus reinforced. In this paper, we model this scenario as a Stackelberg game, where the police department (called defender) allocates resources dynamically in terms of the traffic situation on the traffic network to arrest drink drivers and drivers who drink (called attacker), whether choosing drunk driving or designated driving service, expect to minimize their cost for given travel routes. However, with the number of resources are limited, our goal is to calculate the optimal resource allocation strategy for the defender. Therefore, first, we provide an effective approach (named OISDD) to fulfill our goal, i.e., generate the optimal strategy to inspect drunk driving. Second, we apply OISDD to directed graphs (which are abstracted from Dalian traffic network) to analyze and test its correctness and rationality. The experimental results show that OISDD is feasible and efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.611-627
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• 2017

For enhancing the coverage of wireless networks and increasing the spectrum efficiency, small cell networks (SCNs) are considered to be one of the most prospective schemes. Most of the existing literature on resource allocation among non-cooperative small cell base stations (SBSs) has widely drawn close attention and there are only a small number of the cooperative ideas in SCNs. Based on the motivation, we further investigate the cooperative approach, which is formulated as a coalition formation game with power control algorithm (CFG-PC). First, we formulate the downlink sub-channel resource allocation problem in an SCN as a coalition formation game. Pareto order and utilitarian order are applied to form coalitions respectively. Second, to achieve more availability and efficiency power assignment, we expand and solve the power control using particle swarm optimization (PSO). Finally, with our proposed algorithm, each SBS can cooperatively work and eventually converge to a stable SBS partition. As far as the transmit rate of per SBS and the system rate are concerned respectively, simulation results indicate that our proposed CFG-PC has a significant advantage, relative to a classical coalition formation algorithm and the non-cooperative case.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.17-26
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• 2022

Sensor Nodes play a major role to monitor and sense the variations in physical space in various real-time application scenarios. These nodes are powered by limited battery resources and replacing those resource is highly tedious task along with this it increases implementation cost. Thus, maintaining a good network lifespan is amongst the utmost important challenge in this field of WSN. Currently, energy efficient routing techniques are considered as promising solution to prolong the network lifespan where multi-hop communications are performed by identifying the most energy efficient path. However, the existing scheme suffer from performance related issues. To solve the issues of existing techniques, a novel hybrid technique by merging particle swarm optimization and game theory model is presented. The PSO helps to obtain the efficient number of cluster and Cluster Head selection whereas game theory aids in finding the best optimized path from source to destination by utilizing a path selection probability approach. This probability is obtained by using conditional probability to compute payoff for agents. When compared to current strategies, the experimental study demonstrates that the proposed GTPSO strategy outperforms them.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.121-131
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• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.