• Journal of the Korean Society for Aviation and Aeronautics
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• v.7 no.1
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• pp.77-89
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• 1999

The atmosphere condition at Kimpo International Airport occasionally prevents the aircraft from landing and forces them to fly to an alternate airport, especially in October and November during a year. Many airlines designated foreign airports instead of Korean airports as alternate airports in the case of the bad weather condition preventing use of Kimpo Airport. This paper addresses 1) economic comparison of candidates for the alternate airport, 2) what are the criteria for the alternate airport selection and the relative importance among the criteria and 3) evaluation of candidates for alternate airport using Brown and Gibson's pair-wise comparison method. It is found to be possible to reduce costs related alternate flight by 36% using Korean airports rather than using Japan's Hukuoka Airport. However, airlines weigh more on the factors such as service level of ground handling, accommodation for passengers and ground access convenience than costs. Among Korean airports, Kimhae International Airport is found the most favorable airport as the alternate airport for Kimpo International Airport.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4680-4697
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• 2017

In future, since the user experience plays a more and more important role in the development of today's communication systems, quality of experience (QoE) becomes a widely used metric, which reflects the subjective experience of end users for wireless service. In addition, the energy efficiency is an increasingly important problem with the explosive growth in the amount of wireless terminals and nodes. Hence, a QoE-aware energy efficiency maximization based joint user access selection and power allocation approach is proposed to solve the problem. We transform the joint allocation process to an optimization of energy efficiency by establishing an energy efficiency model, and then the optimization problem is solved by chaotic clone immune algorithm (CCIA). Numerical simulation results indicate that the proposed algorithm can efficiently and reliably improve the QoE and ensure high energy efficiency of networks.

• Korean journal of applied entomology
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• v.28 no.4
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• pp.237-243
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• 1989

These studies were conducted to investigate the development of chemical resistance in two-spotted spider mite (Tetranychus urticae Koch) through alternate selection for a given period of time with four acaricides including ethion of organophophours compound, dicofol of organo-chlorine compound, cyhexatin of organo-tin compound, and biphenthrin of synthetic pyrethroid compound; and to examine multiple-resistance among the acaricides to the selected populations. The development levels of chemical resistance in the two-spotted spider mite were greatly varied under alternate selection with the different chemical-group combination of four acaricides. Resistant levels of the ethion/dicofol-selected population at 13th-13th generation showed 49.4-fold resistance to ethion and 18.1-fold to dicofol; the ethion/cyhexatin-selected population at 9th-9th generation exhibited 28.1-fold to ethion and 5-fold to cyhexatin; the ethion/biphenthrin-selectd population at 10th-10th generation revealed 39.8-fold to ethion and 19.2-fold to biphenthrin. However, the dicofol/cyhexatin-selected population at 9th-9th generation showed 11.3-fold to dicofol and 4.9-fold to cyhexatin, and the dicofol/biphenthrin-selected population at 12th-12th generation exhibited 11.2-fold to dicofol and 9.4- fold to biphenthrin, while the cyhexatin/biphenthrin-selected population at 9th-9th generation revealed 3.7-fold to cyhexatin and 7.7-fold to biphenthrin. In case of alternate selection, the ehtion/dicofol-selected population revealed moderate multiple-resistance level to biphenthrin. The ethion/cyhexatin-selected and the ethion/biphenthrin-selected populations showed low mutiple-resistance level to biphenthrin and dicofol, respectively. However, the dicofol/cyhexatin-selected, the dicofol/biphenthrin-selected and the cyhexatin/biphenthrin-selected populations exhibited high multiple-resistance level to ethion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2177-2193
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• 2018

This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

• Smart Media Journal
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• v.4 no.1
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• pp.52-57
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• 2015

Currently the gamification as marketing technique has appeared in the field non-related with game, applied to game elements. The alternate reality game pulled down the boundary between the real and the virtual has come out. New trend game has shown beyond the range of the existing game. The possibility has import into online baseball simulation game. The objective of this research is the exploratory approach to build GOMS model through three subjects to the famous pro-baseball manager game. After game playing session, three subjects' utterance with game experience was recorded. We built the goal hierarchy of goal in GOMS to pro-baseball manager game to analyze the vocabulary in three subjects' utterance. We try to find the possibility of gamification in alternate reality game interacting between the real and the virtual, and demolishing them.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.56-61
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• 2021

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.316-318
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• 2001

Occasionally, equipment in a distribution system fails due to damage from weather, vandalism, or other causes. In addition, it is recommended practice to have some way in which maintenance or replacement of every element in a system can be performed without causing lengthy interruption of electrical service to the customers it feeds. Thus, alternate sources, paths, and configurations of service must be planned so that both failures and maintenance do not affect customer service beyond a reasonable amount. In some cases, planning for alternate routes of service during equipment outages or emergencies -- will be the major aspect influencing selection of a feeder's capacity, type of route, or layout. We want to know the relationship between molt-dividing multi-connection and distribution reliability for contingency support considerations.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.13-18
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• 2023

This paper aims to investigate data features for neighbor path selection (NPS) in computer network with regional failures. It is necessary to find an available alternate communication path in advance when regional failures due to earthquakes or forest fires occur simultaneously. We describe previous general heuristics and simulation heuristic to solve the NPS problem in the regional fault network. The data features of general heuristics using proximity and sharing factor and the data features of simulation heuristic using machine learning are explained through examples. Simulation heuristic may be better than general heuristics in terms of communication success. However, additional data features are necessary in order to apply the simulation heuristic to the real environment. We propose novel data features for NPS in computer network with regional failures and Keras modeling for computing the communication success probability of candidate neighbor path.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1116-1120
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• 2010

In this paper we present two refined neighbor selection algorithms for recommender systems and also show how the attributes of the items can be used for higher prediction quality. The refined neighbor selection algorithms adopt the transitivity-based neighbor selection method using virtual neighbors and alternate neighbors, respectively. The experimental results show that the recommender systems with the proposed algorithms outperform other systems and they can overcome the large scale dataset problem as well as the first rater problem without deteriorating prediction quality.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.47-62
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• 1992

This paper describes a procedure for optimizing the route selection and production conditions in alternate process plans under a cellular manufacturing environment. The type of production is mainly production-to-order which deals with unexpected products as the changes factor. The flexible cellular manufacturing can be viewed as a complete unification of both flexible manufacturing process and flexible production management. The integrated problem for designing flexible cellular manufacturing associated with determining the optimal values of the machining speeds, overtime, and intercell flow is formulated as Nonlinear Mixed Integer Programming(NMIP) in order to minimize total production change cost. This is achieved by introducing the marginal cost analysis into the NMIP, which will compute the optimal machining speed, overtime, intercell flow, and routing. The application of this procedure offers greater flexibility to take advantage of the cellular manufacturing due to the optimum use of resources. A solution procedure for this problem was developed and a numerical example is included.