• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.769-776
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• 2000

RP(Rapid Prototyping) technology is gaining its popularity in building a prototype in all industries. SLS(Slective Laser Sintering) is one of RP technologies, which is focused on tooling processes as well as three dimension solid model. There are several factors, the length and the cross-sectional area of a part, that have an effect on build setup in SLS process. In this paper, the computation on geometrical relationship is used to slice STL file and to estimate these factors. Based on these values, the build setup parameters such as the heating temperature, the laser power, and the powder cartridge feed rate are determined by neural network approaches. The test results show that the computation time is saved and the neural network approach is able to apply to get the optimal parameters of build process within an acceptable error rate.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.363-370
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• 2002

A substrate network model characterizing substrate effect of submicron MOS transistors for RF operation and its parameter extraction with physically meaningful values are presented. The proposed substrate network model includes a single resistance and inductance originated from ring-type substrate contacts around active devices. Model parameters are extracted from S-parameter data measured from common-bulk configured MOS transistors with floating gate and use where needed with out any optimization. The proposed modeling technique has been applied to various-sized MOS transistors. Excellent agreement the measurement data and the simulation results using extracted substrate network model up to 30GHz.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.307-310
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• 2011

IPTV의 스트리밍 서비스를 위해 P2P를 이용하는 방법이 활발하게 연구되어지고 있다. 이 논문에서는 topology를 최적화하는 방안으로 P2P에서 각 peer 간에 연결 및 전송 정보를 이용하는 방법을 제안한다. 제안하는 방법은 mesh-network에서 각 peer에 연결된 link의 수를 이용하여 업로드 대역폭을 추정하는 알고리즘을 기반으로 한다. 이 방법은 자원의 관리를 위해 업로드 대역폭을 판단하기 위한 메시지 과부하를 효과적으로 줄여주지만 스트리밍에서 주어진 연산만을 수행할 경우 업로드 대역폭과 무관한 형태로 network topology가 잘못 구성될 가능성을 가지고 있다. 본 논문에서는 기존 연구에서 부족했던 부분들을 정리하고 극복할 수 있는 각각의 알고리즘들과 적용했을 시에 예상되는 결과를 제시한다.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.895-904
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• 2015

This paper presents a probabilistic approach of reliability evaluation and economic assessment for solving transmission network expansion planning problems. Three methods are proposed for TNEP, which are reorganizing the existing power system focused on the buses of interest, selecting candidates using modified system operating state method with healthy, marginal and at-risk states, and finally choosing the optimal alternative using cost-optimization method. TNEP candidates can be selected based on the state reliability such as sufficient and insufficient indices, as proposed in this paper. The process of economic assessment involves the costs of construction, maintenance and operation, congestion, and outage. The case studies are carried out with modified IEEE-24 bus system and Jeju island power system expansion plan in Korea, to verify the proposed methodology.

• Industrial Engineering and Management Systems
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• v.10 no.3
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• pp.221-231
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• 2011

One of the critical issues in wireless sensor network is the design of a proper routing protocol. One possible approach is utilizing a virtual infrastructure, which is a subset of sensors to connect all the sensors in the network. Among the many virtual infrastructures, the connected dominating set is widely used. Since a small connected dominating set can help to decrease the protocol overhead and energy consumption, it is preferable to find a small sized connected dominating set. Although many algorithms have been suggested to construct a minimum connected dominating set, there have been few exact approaches. In this paper, we suggest an improved optimal algorithm for the minimum connected dominating set problem, and extensive computational results showed that our algorithm outperformed the previous exact algorithms. Also, we suggest a new heuristic algorithm to find the connected dominating set and computational results show that our algorithm is capable of finding good quality solutions quite fast.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.3
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• pp.45-52
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• 2006

Burrs formed during face milling operations can be very difficult to characterize since there exist several parameters which have complex combined effects that affect the cutting process. Many researchers have attempted to predict burr characteristics including burr size and shape, using various experimental parameters such as cutting speed, feed rate, in-plane exit angle, and number of inserts. However, the results of these studies tend to be limited to a specific process parameter range and to certain materials. In this paper, the Taguchi method, a systematic optimization method for design and analysis of experiments, is introduced to acquire optimum cutting conditions for burr minimization. In addition, an in process monitoring scheme using an artificial neural network is presented for the prediction of burr types.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.63-68
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• 2015

Pattern layout design is very important to the automation of apparel industry. Until now, the genetic algorithm and Tabu search method have been applied to layout design automation. With the genetic algorithm and Tabu search method, the obtained values are not always consistent depending on the initial conditions, number of iterations, and scheduling. In addition, the selection of various parameters for these methods is not easy. This paper presents a hybrid search method that uses a neural network and simulated annealing to solve these problems. The layout of pattern elements was optimized to verify the potential application of the suggested method to apparel pattern layout design.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.38-43
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• 2008

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.113-125
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• 2004

The network disconnection problem ms to find a set of edges such that the total cost of removing the edges is no more than a given budget and the weight of nodes disconnected from a designated source by removing edges is maximized. Martel et at. have shown that the problem with unit capacity and unit demand Is NP-hard and Myung and kim present an integer programming formulation and develop an algorithm that Includes a preprocessing procedure and lower and upper bounding strateagies. in this paper, we present new findings on the properties of the optimal solution and an alternative integer programming formulation, based on which new lower and upper bounding strategies are developed. Computational results for evaluating the performance of the proposed algorithm are also presented.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.1
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• pp.129-136
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• 2006

A new guidance synthesis for anti-ship missiles to control impact angle and impact time is proposed in this paper. The flight vehicle is assumed as a 1st order lag system to consider more practical system. The proposed guidance synthesis enhances the survivability of anti-ship missiles because multiple anti-ship missiles with the proposed synthesis can hit the target simultaneously. The control input to satisfy constraints of zero miss distance and impact angle, and the feedforward bias control input to control impact time constitute the guidance law. The former is from trajectory shaping guidance, the latter is from neural network. And particle swarm optimization method is introduced to furnish reference input and output for learning in neural network. The performance of the proposed synthesis in the accuracy of impact time and angle is validated by numerical examples.