• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.930-939
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• 2021

In recent years, the use of broadband bandwidth and redundant links for stable transmission in networks has resulted in excessive energy consumption and reduced transmission efficiency. In this paper, we propose an optimization algorithm that reduces the number of transmission links and minimizes transmission energy by removing redundant traffic in networks where traffic redundancy is allowed. The optimization algorithm proposed in this paper uses the meta-heuristic method using Tabu search algorithm. The proposed optimization algorithm minimizes transmission energy by designing a neighborhood generation method that efficiently routes overlapping traffic. The performance evaluation of the proposed optimization algorithm was performed in terms of the number of links used to transmit all traffic generated in the network and the transmission energy consumed. From the performance evaluation results, it was confirmed that the proposed algorithm is superior to other algorithms previously proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.201-209
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• 2014

This paper proposes a genetic algorithm to maximize the connectivity among the mobile nodes for the cooperative communication in ad-hoc networks. In general, as the movement of the mobile nodes in the networks increases, the amount of calculation for finding the solution would be too much increased. To obtain the optimal solution within a reasonable computation time for a high-density network, we propose a genetic algorithm to obtain the optimal solution for maximizing the connectivity. In order to make a search more efficient, we propose some efficient neighborhood generating operations of the genetic algorithm. We evaluate those performances through some experiments in terms of the maximum number of connections and the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms other existing algorithms.

• Journal of the Society of Naval Architects of Korea
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• v.37 no.3
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• pp.90-98
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• 2000

Nesting and cutting path optimization have a great effect on price competitions and improvement of productivity in various industries such as the shipbuilding, the auto, the clothing, and so on. But the theoretical approach on the development of cutting path optimization algorithm, which can be applied effectively in the shipbuilding, has not been performed enough because parts are so complex and various. In this study, a new solution has been presented to solve the cutting path problem in 2-D cutting by using improved genetic algorithm. The presented optimization algorithm can search not only the cutting sequence of parts but also the position of piercing point by applying the effective neighborhood solution generating method

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.8-17
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• 2005

This paper dealt with a kind of heterogeneous vehicle routing problem with known demand and time deadline of customers. The customers are supposed to have one of tight deadline and loose deadline. The demand of customers with tight deadline must be fulfilled in the deadline. However, the late delivery is allowed to customers with loose deadline. That is, the paper suggests a model to minimize total acquisition cost, total travel distance and total violation time for a fleet size and mix vehicle routing problem with time deadline, and proposes a heuristic algorithm for the model. The proposed algorithm consists of two phases, i.e. generation of an initial solution and improvement of the current solution. An initial solution is generated based on a modified insertion heuristic and iterative Improvement procedure is accomplished using neighborhood generation methods such as swap and reallocation. The proposed algorithm is evaluated using a well known numerical example.

• The Journal of Korean Society for School & Community Health Education
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• v.7
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• pp.87-99
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• 2006

Objectives: This study is to draw the design of the program which is improve school health promotion participation by applying the Social Ecological Model based on the literature review on the health promotion. Methods: Literature review was carried out based on 5 factors of social ecological model using computer search engines of Google, ProQuest, and Riss4U. Results; Social Ecological Model is consist of individual, interpersonal, institutional/organizational, community, and policy. Individual sphere is drawn from Health Belief Model, interpersonal sphere is Social Support Theory, institutional/ organizational sphere is institutional resources theory, community sphere is community model, and policy sphere is Social Marketing Theory. The literature review show that the important variables affecting health promotion exist in each sphere. Individual sphere has social economic status, age, sex, sensitivity and specificity of illness, self-efficacy. Interpersonal sphere has support and use of family, friend and neighbor. Institutional/Organizational sphere has environment service reliability and utility. Conclusions: Community sphere has distance, neighborhood safety, interrelationship among institutions. Policy sphere has cost, legislation advertisement, lobby and concern and leadership of Institution.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.389-394
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• 2002

In this paper, we propose a robust stereo matching algorithm using nonlinear extended Kalman filter. The proposed algorithm estimates disparity using nonlinear extended Kalman filter and compares left image to right image for obtained disparity. As this process is run iteratively, we get disparity only with a few search. And, we can get robust stereo matching results by comparing left image to right image using bilinear interpolation to consider influence of neighborhood pixel. We compared SSD algorithm which is widely used, in stereo matching method, to result of the proposed algorithm. As the result, the proposed algorithm has an outstanding matching performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.869-873
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• 2008

Optimization method for the open loop commutation time intervals in HDD spindle start-up control is presented in this paper. A hard disk drive(HDD) uses a sensorless brushless DC motor(BLDC) for the platter rotation. Because there is no direct sensor for the rotor position, open loop commutations after sensing the rotor position at a standstill using inductive sensing method are performed to speed up the rotor up to a certain speed where the zero crossings of the back electromotive force(EMF) are measurable. Therefore successful open loop commutations are necessary for the stable start-up control of the spindle motors. Random neighborhood search(RNS) algorithm is introduced as a optimization technic in this paper. Rotor speed and its standard deviation are used as a cost function and commutation intervals obtained from the spindle motion equation are used as initial parameter values for the RNS. With the help of the proposed method optimized open loop commutation time intervals for the very low start-up current are acquired and tested. The experimental results shows that the proposed method can decrease the start-up failure rate of a HDD spindle motor.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.85-95
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• 2003

This paper proposes a multiple moving objects tracking system which is adaptable itself to circumstances. Snake model is sensitive to the start position value because it does not accurately express contours of objects in complex image. It can be improved as the proposed system gets background images by using difference images, segments objects using neighborhood pixels and assesses the position feature values acquired on the start position value to deformable Snake model. And also the system can simplify complex background images and reduce search regions by the constituent points of a Snake laid in Positions of object. It is showed that the proposed system can be appBied to multiple moving vehicle racking systems by the experimental results of 30fps AVI file.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1715-1724
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• 2013

The maximum lifetime data aggregation problem is to maximize the network lifetime as minimizing the transmission energy of all deployed nodes in wireless sensor networks. In this paper, we propose a simulated annealing algorithm to solve efficiently the maximum lifetime data aggregation problem on the basis of meta-heuristic approach in wireless sensor networks. In order to make a search more efficient, we propose a novel neighborhood generating method and a repair function of the proposed algorithm. We compare the performance of the proposed algorithm with other existing algorithms through some experiments in terms of the network lifetime and algorithm computation time. Experimental results show that the proposed algorithm is efficient for the maximum lifetime data aggregation problem in wireless sensor networks.

• Journal of Information Technology Services
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• v.7 no.3
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• pp.71-85
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• 2008

The rapid growth of blog has caused information overload where bloggers in the virtual community space are no longer able to effectively choose the blogs they are exposed to. Recommender systems have been widely advocated as a way of coping with the problem of information overload in e-business environment. Collaborative Filtering (CF) is the most successful recommendation method to date and used in many of the recommender systems. In this research, we propose a CF-based recommender system for bloggers to find their similar bloggers or preferable virtual community without burdensome search effort. For such a purpose, we apply the "Interest Value" to CF recommender systems. The Interest Value is the quantity value about users' transaction data in virtual community, and can measure the opinion of users accurately. Based on the Interest Value, the neighborhood group is generated, and virtual community list is recommended using the Community Likeness Score (ClS). Our experimental results upon real data of Korean Blog site show that the methodology is capable of dealing with the information overload issue in virtual community space. And Interest Value is proved to have the potential to meet the challenge of recommendation methodologies in virtual community space.