• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.199-202
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• 2005

In this paper, the six sigma scheme is employed together with the rigid-viscoplastic finite element method to obtain the optimal metal flow lines in hot press forging. In general, the six sigma process is consisted of following five steps : define, measure, analyze, improve and control. Each step Is investigated in detail to meet customer's requirements through improvement of product quality. A forging simulator, AFDEX-2D, is used for analysis of the metal flow lines of a multi-stage hot forging process under various conditions of major factors, determined at each step of the six sigma process. The analyzed results are examined in order to reveal the effects of major factors on the metal flow lines and the formed shapes. The effects are used to find an optimal process and the optimal process with die is devised and tested. The comparison between required metal flow lines and experiments shows that the approach is effective for optimal process in hot forging design considering metal flow lines.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.383-403
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• 2021

With the development of mobile edge computing (MEC), some late-model application technologies, such as self-driving, augmented reality (AR) and traffic perception, emerge as the times require. Nevertheless, the high-latency and low-reliability of the traditional cloud computing solutions are difficult to meet the requirement of growing smart cars (SCs) with computing-intensive applications. Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency. To solve this problem with effect, we propose a context-aware offloading strategy based on differential evolution algorithm (DE) by considering vehicle mobility, roadside units (RSUs) coverage, vehicle priority. On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. Simulation results demonstrate that the practical performance of the context-aware vehicular task offloading (CAVTO) optimization scheme could reduce the system delay significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1123-1140
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• 2019

Many Internet of Things (IoT) applications involving bursty traffic have emerged recently with event detection. A power management scheme qualified for uplink bursty traffic (PM-UBT) is proposed by distinguishing between bursty and general uplink traffic patterns in the IEEE 802.11 standard to balance energy consumption and uplink latency, especially for stations with limited power and constrained buffer size. The proposed PM-UBT allows a station to transmit an uplink bursty frame immediately regardless of the state. Only when the sleep timer expires can the station send uplink general traffic and receive all downlink frames from the access point. The optimization problem (OP) for PM-UBT is power consumption minimization under a constrained buffer size at the station. This OP can be solved effectively by the bisection method, which demonstrates a performance similar to that of exhaustive search but with less computational complexity. Simulation results show that when the frame arrival rate in a station is between 5 and 100 frame/second, PM-UBT can save approximately 5 mW to 30 mW of power compared with an existing power management scheme. Therefore, the proposed power management strategy can be used efficiently for delay-intolerant uplink traffic in event-driven IoT applications, such as health status monitoring and environmental surveillance.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.13-23
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• 2008

The pricing/lot-sizing problem of determining the robust optimal order quantity and selling price is discussed. The uncertainty of parameters characterized by an ellipsoid is explicitly incorporated into the problem. An approximation scheme is proposed to transform the problem into a geometric program, which can be efficiently and reliably solved using interior-point methods.

• Journal of the Korea Convergence Society
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• v.5 no.4
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• pp.163-169
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• 2014

A stable neural network control scheme for unknown non-linear systems is developed in this paper. While the control variable is optimised to minimize the performance index, convergence of the index is guaranteed asymptotically stable by a Lyapnov control law. The optimization is achieved using a gradient descent searching algorithm and is consequently slow. A fast convergence algorithm using an adaptive learning rate is employed to speed up the convergence. Application of the stable control to a single input single output (SISO) non-linear system is simulated. The satisfactory control performance is obtained.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.151-164
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• 2001

In this paper, a new approach for finding the approximate solution of the Stokes problem is introduced. In this method the problem is transformed to an equivalent optimization problem. Then, by considering it as a distributed parameter control system, the theory of measure is used to approximate values of pressure are obtained by a finite difference scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.6
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• pp.506-513
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• 2000

This paper proposes a path planning algorithm for dispensers to increase the productivity in printed circuit board assembly lines. We analyze the assembly sequence of the dispenser, and formulate it as an integer programming problem. The mathematical formulation can accomodate multiple heads and different types of heads through extended cost matrix. The TSP algorithms are then applied to the formulated problem to find the near-optimal solution. Simulation results are presented to verify the usefulness of the proposed scheme.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.553-555
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• 2002

현재 화상 또는 음성 회의와 같은 네트워크에 기반한 응용들의 증가와 함께 멀티캐스트 서비스의 중요성이 한층 증가되었다. Xcast는 멀티캐스트 서비스를 제공하기 새롭게 제안된 방법이고, XMIF는 MIPv4와 MIPv6 환경에서 Xcast를 이용해서 멀티캐스트 서비스를 제공하기 위한 방법이다. 하지만 XMIFv4에서는 MIP가 가지는 Triangle Routing 문제를 그대로 가지고 있고 이동 중 심각한 패킷 손실이 발생 할 수 있다. 또한 QoS를 제공하기 위해 RSVP와 같은 프로토콜을 함께 사용할 때 확장성이 용이하지 않다. 따라서, 본 논문에서는 MIPv4 환경에서 XMIPv4가 가지는 문제를 해결하기 위한 방법으로 XMIPRO를 제안한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.358-363
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• 1992

A two-dimensional static biomechanical model of lower extremity in the seated posture was developed to assess muscular activities of lower extremity required for a variety of foot pedal operations. Muscle forces of the model were predicted using the double linear optimization scheme. For the model validation, three subjects performed the experiments which measured EMG activities of six lower extremity muscles. Predicted muscle forces were compared with the corresponding rectified intergrated EMG amplitudes and it showed reasonable results.