• Title/Summary/Keyword: Selecting action

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Characteristics of transmission control of an AMT vehicle (AMT 차량의 변속제어 특성에 관한 연구)

  • Kong Jin-Young;Song Chang-Seop
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.3 s.180
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    • pp.86-93
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    • 2006
  • This study is concerned with the investigation of characteristics of an AMT (Automated Manual Transmission) which are composed of clutch part and transmission part. When a shilling signal is received from the controller, the clutch is disengaged first, and shifting action including selecting action is followed, and then the clutch is engaged last. The characteristics of transmission shifting response are affected by various parameters of clutch and transmission control elements. Analytical results are in fair agreement with experimental results. It is found that the operating pressure level is the most important for the response of AMT characteristics, and that the other parameters such as natural frequency and damping ratio of the control valve are less important.

Corrective Action Strategy based on SWOT Analysis in Service FMEA (SWOT분석을 토대로 한 서비스 FMEA에서의 개선조치전략)

  • Sutrisno, Agung;Kwon, Hyuck-Moo
    • Journal of Korean Society for Quality Management
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    • v.40 no.1
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    • pp.25-38
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    • 2012
  • Service FMEA may yield several possible corrective actions for each failure mode with large RPN. Corrective actions for each service failure are usually interrelated with the customers and environmental elements of the service system. SWOT analysis can provide an effective way to analyze the inner and outer environmental impacts for each corrective action. In this paper, we suggest a way for selecting and ranking corrective strategy in service operation based on SWOT analysis. Every candidate of corrective action strategy is ranked and evaluated on the basis of the impact factors of the SWOT variables, correlations between possible corrective actions and SWOT variables, and RPNs of service failures. The most desirable set of corrective actions is selected considering the preference score of each corrective action, required resources and budgetary allowance. The proposed methodology is demonstrated with an illustrative example.

An Analysis of Action Learning Process in Education Programs for Senior Officials, Engineers, Chief Executive Officers (고위공직 후보자-엔지니어-최고경영자 교육 프로그램의 액션러닝 프로세스 분석)

  • Jung, Hyun-Kon;Moon, Sung-Han
    • Journal of Digital Convergence
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    • v.10 no.1
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    • pp.87-104
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    • 2012
  • The purpose of this study was to analyze and present of action learning process in education programs for senior officials, engineers, chief executive officers. The main contents of this study is focused on analysis of orientation activities for each step of action learning process, project selection, analysis of problem clarification, review of data research and analysis, analysis of process for seeking of alternative and selecting execution item, comparison and analysis for the results of execution.

A situation-Flexible and Action-Oriented Cyber Response Mechanism against Intelligent Cyber Attack (지능형 사이버공격 대비 상황 탄력적 / 실행 중심의 사이버 대응 메커니즘)

  • Kim, Namuk;Eom, Jungho
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.16 no.3
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    • pp.37-47
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    • 2020
  • The In the 4th industrial revolution, cyber space will evolve into hyper-connectivity, super-convergence, and super-intelligence due to the development of advanced information and communication technologies, which will connect the nation's core infrastructure into a single network. As applying the 4th industrial revolution technology to the cyber attack technique, it is evolving in an intelligent and sophisticate method. In order to response intelligent cyber attacks, it is difficult to guarantee self-defense in cyberspace by policy-oriented, preplanned-centric and hierarchical cyber response strategies. Therefore, this research aims to propose a situation-flexible & action-oriented cyber response mechanism that can respond flexibly by selecting the most optimal smart security solution according to changes in the cyber attack steps. The proposed cyber response mechanism operates the smart security solutions according to the action-oriented detailed strategies. In addition, artificial intelligence-based decision-making systems are used to select the smart security technology with the best responsiveness.

Seamless Mobility of Heterogeneous Networks Based on Markov Decision Process

  • Preethi, G.A.;Chandrasekar, C.
    • Journal of Information Processing Systems
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    • v.11 no.4
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    • pp.616-629
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    • 2015
  • A mobile terminal will expect a number of handoffs within its call duration. In the event of a mobile call, when a mobile node moves from one cell to another, it should connect to another access point within its range. In case there is a lack of support of its own network, it must changeover to another base station. In the event of moving on to another network, quality of service parameters need to be considered. In our study we have used the Markov decision process approach for a seamless handoff as it gives the optimum results for selecting a network when compared to other multiple attribute decision making processes. We have used the network cost function for selecting the network for handoff and the connection reward function, which is based on the values of the quality of service parameters. We have also examined the constant bit rate and transmission control protocol packet delivery ratio. We used the policy iteration algorithm for determining the optimal policy. Our enhanced handoff algorithm outperforms other previous multiple attribute decision making methods.

Subjective Point Prediction Algorithm for Decision Analysis

  • Kim, Soung-Hie
    • Journal of the Korean Operations Research and Management Science Society
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    • v.8 no.1
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    • pp.31-40
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    • 1983
  • An uncertain dynamic evolving process has been a continuing challenge to decision problems. The dynamic random variable (drv) changes which characterize such a process are very important for the decision-maker in selecting a course of action in a world that is perceived as uncertain, complex, and dynamic. Using this subjective point prediction algorithm based on a modified recursive filter, the decision-maker becomes to have periodically changing plausible points with the passage of time.

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A Fuzzy BOXES Scheme for the Cartpole Control

  • Kwon, Sung-Gyu
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1710-1715
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    • 2005
  • Two fuzzy controllers are coordinated to control a cartpole such that the pole is balanced as well as the cart is brought back to the track origin. The coordination is due to the BOXES scheme that is established through the evaluation of the outcomes of the control action by one of the fuzzy controllers. It is found that the control scheme is good at selecting proper fuzzy controller so that the pole is balanced fast while the cart moves back to the track origin steadily.

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Design of Snubber for PWM Inverter (PWM 인버터용 SNUBBER 설계)

  • 오진석
    • Journal of the Korean Society of Safety
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    • v.8 no.4
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    • pp.95-100
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    • 1993
  • In power transistor switching circuit have shunt snubber(dv/dt limiting capacitor) and series snubber (di/dt limiting inductor). The shunt snubber is used to reduce the turn-off switching loss and the series snubber is used to reduce the turn-on switching loss. Design procedures are derived for selecting the capacitance, inductor and resistance to limit the peak voltage and current values. The action of snubber is analyzed and applied to the design for safety PWM inverter.

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A Simulation Sample Accumulation Method for Efficient Simulation-based Policy Improvement in Markov Decision Process (마르코프 결정 과정에서 시뮬레이션 기반 정책 개선의 효율성 향상을 위한 시뮬레이션 샘플 누적 방법 연구)

  • Huang, Xi-Lang;Choi, Seon Han
    • Journal of Korea Multimedia Society
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    • v.23 no.7
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    • pp.830-839
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    • 2020
  • As a popular mathematical framework for modeling decision making, Markov decision process (MDP) has been widely used to solve problem in many engineering fields. MDP consists of a set of discrete states, a finite set of actions, and rewards received after reaching a new state by taking action from the previous state. The objective of MDP is to find an optimal policy, that is, to find the best action to be taken in each state to maximize the expected discounted reward of policy (EDR). In practice, MDP is typically unknown, so simulation-based policy improvement (SBPI), which improves a given base policy sequentially by selecting the best action in each state depending on rewards observed via simulation, can be a practical way to find the optimal policy. However, the efficiency of SBPI is still a concern since many simulation samples are required to precisely estimate EDR for each action in each state. In this paper, we propose a method to select the best action accurately in each state using a small number of simulation samples, thereby improving the efficiency of SBPI. The proposed method accumulates the simulation samples observed in the previous states, so it is possible to precisely estimate EDR even with a small number of samples in the current state. The results of comparative experiments on the existing method demonstrate that the proposed method can improve the efficiency of SBPI.