• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.3
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• pp.437-444
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• 2014

In this paper, we introduce a Graph based Binary Code Execution Path Exploration Platform. In the graph, a node is defined as a conditional branch instruction, and an edge is defined as the other instructions. We implemented prototype of the proposed method and works well on real binary code. Experimental results show proposed method correctly explores execution path of target binary code. We expect our method can help Software Assurance, Secure Programming, and Malware Analysis more correct and efficient.

• Information Systems Review
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• v.2 no.1
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• pp.13-23
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• 2000

• Journal of Communications and Networks
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• v.9 no.4
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• pp.490-498
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• 2007

BGP route flap damping(RFD) was anecdotally considered to be a key contributor to the stability of the global Internet inter-domain routing system. However, it was recently shown that RFD can incorrectly suppress for substantially long periods of time relatively stable routes, i.e., routes that only fail occasionally. This phenomenon can be attributed to the complex interaction between BGP path exploration and how the RFD algorithm identifies route flaps. In this paper we identify a distinct characteristic of BGP path exploration following a single network event such as a link or router failure. Based on this characteristic, we distinguish BGP route updates during BGP path exploration from route flaps and propose a novel BGP route flap damping algorithm, RFD+. RFD+ has a number of attractive properties in improving Internet routing stability. In particular, it can correctly suppress persistent route flaps without affecting routes that only fail occasionally. In addition to presenting the new algorithm and analyzing its properties, we also perform simulation studies to illustrate the performance of the algorithm.

• Journal of Korea Game Society
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• v.15 no.4
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• pp.157-168
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• 2015

The difficulty of the game is closely related to the fun of the game. However, it is not easy to determine the appropriate level of difficulty of the game. In most cases, human playtesting is required. But even so, it is still hard to quantitatively evaluate difficulty of the game. Thus, if we perform quantitative evaluation of the difficulty automatically it will be very helpful in game developments. In this paper, we use a path finding algorithm to evaluate difficulty of exploration in a game level. Exploration is a basic attribute in common video games and it represents the overall difficulty of the game level. We also optimize the proposed evaluation algorithm by using previous exploration histories when available area in an game level is dynamically expanded and the new search is required.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.687-693
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• 2012

In this paper, we propose a optimal deployment method for cooperative exploration of swarm robots. The proposed method consists of two parts such as optimal deployment and path planning. The optimal area deployment is proposed by the K-mean Algorithm and Voronoi tessellation. The path planning is proposed by the potential field method and A* Algorithm. Finally, the numerical experiments demonstrate the effectiveness and feasibility of the proposed method.

• Journal of Korean society of Dental Hygiene
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• v.13 no.1
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• pp.61-68
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• 2013

Objectives : The purpose of this research is to identify the effect of Dental Hygienic students' level of satisfaction towards their major and sense of career exploration efficacy on their career exploration behavior so that the key findings of this research will help the university students to explore career related to their major and to assume rational attitude towards their career path. Methods : The study was conducted targeting 450 university students who are studying in the Department of Dental Hygienic at the four universities located in Daegu, Gyeongsangbuk-do and Chungcheongbuk-do. Data collection was carried out using the self-administered questions based on the use of structured survey questionnaire, and analysis was conducted using frequency analysis, descriptive statistics, ANOVA, correlation analysis, and multiple regression analysis. Results : 1. Total grade of the Dental Hygienic students' level of satisfaction towards their major was $3.36{\pm}.49$ points, while total grade of the sense of career exploration efficacy was $3.06{\pm}.46$ points. In case of the career exploration behavior, the total grade was $2.76{\pm}.53$ points. 2. In case of the level of satisfaction towards their major, there was a significant difference depending on the class, grade and motivation for admission. As for the sense of career exploration efficacy and career exploration behavior, there was a significant difference depending on grade. 3. Sense of career exploration efficacy and career exploration behavior demonstrated level of satisfaction towards their major manifested positive correlation. Sense of career exploration efficacy manifested positive correlation career exploration behavior. 4. As for the elements that affect Dental Hygienic students' career exploration behavior, they were level of satisfaction towards their major and sense of career exploration efficacy, and the explanatory power was 19.0%. Conclusions : It should be necessary to study the elements that affect Dental Hygienic students' career exploration behavior in greater depth using diverse methods and information in order to increase sense of career exploration efficacy so that the individual Dental Hygienic students can engage in detailed career exploration behavior for the sake of their career path.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.243-253
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• 2019

First steps of Planetary exploration are usually conducted with the use of autonomous rovers. These rovers are capable of finding its own path and perform experiments about the planet's surface. This paper makes a proposal for a multi-agent system which effectively take the advantage of a blackboard system for share knowledge and effort of each agent. Agents use Reactive Model with the combination of Belief Desire Intension (BDI) Model and also use a Path Finding Algorithm for calculate shortest distance and a path for travel on the planet's surface. This approach can perform a surface exploration on a given terrain within a short period of time. Information which are gathered on the blackboard are used to make an output with detailed surface soil variance results. The developed Multi-Agent system performed well with different terrain sizes.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.1
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• pp.102-109
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• 2015

In Korea, Lunar exploration program has been prepared with the aim of launching in the 2020's. As a part of it, a lunar lander demonstrator was developed, which was the model for verifying the system such as structure, propulsion, and control system, before launching into the deep space. This paper deals with the path tracking performance of the lunar lander demonstrator with respect to the thruster controller based on Pulse Width Pulse Frequency Modulator (PWPFM) and Pulse Width Modulator (PWM). First, we derived equations of motion, considering the allocation of the thrusters, and designed the path tracking controller based on Euler angle. The signal generated from the path tracking controller is continuous, so PWPFM and PWM modulator are adopted for generating ON/OFF signal. Finally, MATLAB simulation is performed for evaluating the path tracking ability. We compared the path tracking performances of PWPFM and PWM based thrust controller, using performance measures such as the total impulse and the position error with respect to the desired path.

• ETRI Journal
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• v.38 no.6
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• pp.1240-1249
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• 2016

With the number of IP cores in a multicore system-on-chip increasing to up to tens or hundreds, the role of on-chip interconnection networks is vital. We propose a networks-on-chip-style bus network as a compromise and redefine the exploration problem to find the best IP tiling patterns and communication path combinations. Before solving the problem, we estimate the time complexity and validate the infeasibility of the solution. To reduce the time complexity, we propose two fast exploration algorithms and develop a program to implement these algorithms. The program is executed for several experiments, and the exploration time is reduced to approximately 1/22 and 7/1,200 at the first and second steps of the exploration process, respectively. However, as a trade-off for the time saving, the time cost (TC) of the searched architecture is increased to up to 4.7% and 11.2%, respectively, at each step compared with that of the architecture obtained through full-case exploration. The reduction ratio can be decreased to 1/4,000 by simultaneously applying both the algorithms even though the resulting TC is increased to up to 13.1% when compared with that obtained through full-case exploration.

• Journal of IKEEE
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• v.23 no.4
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• pp.1150-1156
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• 2019

This paper explores a model-free value-based approach for solving survival gridworld problem. Survival gridworld problem opens up a challenge involving taking risks to gain better rewards. Classic value-based approach in model-free reinforcement learning assumes minimal risk decisions. The proposed method involves a hybrid on-policy and off-policy updates to experience roll-outs using a modified Q-based update equation that introduces a parametric linear rectifier and motivational discount. The significance of this approach is it allows model-free training of agents that take into account risk factors and motivated exploration to gain better path decisions. Experimentations suggest that the proposed method achieved better exploration and path selection resulting to higher episode scores than classic off-policy and on-policy Q-based updates.