• Journal of Distribution Science
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• v.16 no.12
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• pp.95-104
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• 2018

Purpose - In order to gain the upper hand in competition between container terminals, efforts to improve container terminal productivity continue. Export containers arrive randomly in the container terminal and are carried in the container terminal yard according to the arrival order. On the other hand, containers are carried out of the container terminal yard in order based on container weight, not in order of arrival. Because the carry-in order and the carry-out order are different, rehandling may occur, which reduces the performance of the container terminals. In order to reduce rehandling number, containers can be moved in advance when they arrive, which is called preprocessing. This paper proposes an effective preprocessing algorithm and analyzes the factors that affect the productivity of the container terminals. It also provides a way to choose the best factors for preprocessing for a variety of situations. Research design, data, and methodology - To analyze the impact of factors affecting the performance of preprocessing algorithms presented in this paper, simulations are performed. The simulations are performed for two types of bays, 12 stacks with 8 tiers, and 8 stacks with 6 tiers. Results - The results of the factor analysis that affects the performance of the preprocessing algorithm were as follows. (1) As the LMF increased, preprocessing number increases and rehandling number decreased. (2) The LML effect was greatest when the LML changed from 0 to 1, and that the effect decreased when it changed above 1. (3) The sum of preprocessing number and rehandling number was then shown to be increased after decrease, as the LMF increased. (4) In the case of NCI, a decrease in NCI showed that the containers would become more grouped and thus the performance was improved. (5) There was a positive effect in the case of EFS. Conclusion - In this paper, preprocessing algorithm was proposed and it was possible to choose the best factors for preprocessing for a variety of situations through simulations. Further research related to this study needs to be carried out in the following topic : a study on the improvement of container performance by connecting the preprocessing with remarshalling.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.865-868
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• 2000

In this paper we derive a new VAD algorithm, which combines the preprocessing algorithm and the optimum decision rule. To improve the performance of the VAD algorithm we employ the speech enhancement algorithm and then apply the maximal ratio combining technique in the preprocessing procedure, which leads to maximized output SNR. Moreover, we also perform extensive computer simulations to demonstrate the performance improvement of the proposed algorithm under various background noise environments.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.1
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• pp.117-129
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• 2008

Make-to-order manufacturers with multiple plants at multiple sites need to have the ability to quickly determine which plant will produce which customer order to meet the due date and minimize the transportation cost from the plants to the customer. Balancing the work loads and minimizing setups and make-span are also of great concern. Solving such scheduling problems usually takes a long time. We propose a new approach, which we call 'preprocessing', for resolving such complex problems. In preprocessing scheme, a 'good' a priori schedule is prepared and maintained using unconfirmed order information. Upon the confirmation of orders. the preprocessed schedule is quickly modified to obtain the final schedule. We present a preprocessing solution algorithm for multi-site constraint scheduling problem (MSCSP) using genetic algorithm; and conduct computational experiments to evaluate the performance of the algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.105-108
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• 1997

Previous studies in stock market predictions using artificial intelligence techniques such as artificial neural networks and case-based reasoning, have focused mainly on spot market prediction. Korea launched trading in index futures market (KOSPI 200) on May 3, 1996, then more people became attracted to this market. Thus, this research intends to predict the daily up/down fluctuant direction of the price for KOSPI 200 index futures to meet this recent surge of interest. The forecasting methodologies employed in this research are the integration of genetic algorithm and artificial neural network (GAANN) and the integration of genetic algorithm and case-based reasoning (GACBR). Genetic algorithm was mainly used to select relevant input variables. This study adopts the categorical data preprocessing based on expert's knowledge as well as traditional data preprocessing. The experimental results of each forecasting method with each data preprocessing method are compared and statistically tested. Artificial neural network and case-based reasoning methods with best performance are integrated. Out-of-the Model Integration and In-Model Integration are presented as the integration methodology. The research outcomes are as follows; First, genetic algorithms are useful and effective method to select input variables for Al techniques. Second, the results of the experiment with categorical data preprocessing significantly outperform that with traditional data preprocessing in forecasting up/down fluctuant direction of index futures price. Third, the integration of genetic algorithm and case-based reasoning (GACBR) outperforms the integration of genetic algorithm and artificial neural network (GAANN). Forth, the integration of genetic algorithm, case-based reasoning and artificial neural network (GAANN-GACBR, GACBRNN and GANNCBR) provide worse results than GACBR.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.28A no.5
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• pp.347-354
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• 1991

In this paper, the Automatic Tracking Window(ATW) algorithm is applied to the Generalized Cross-Correlation(GCC) time delay estimation algorithm as a preprocessing. The Linear Prediction(LP) algorithm, which is a pararmetric spectral estimation algorithm, is applied to the time delay estimation. And the ATW, a preprocessing algorithm is applied to this algorithm too. This paper shows that the ATW algorithm attenuates the sidelobes very much and improves the resolution of the timedelay estimation.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.1002-1005
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• 1995

This paper presents an enhanced preprocessing and recognition algorithm for automatic vehicle license plate recognition system. The algorithm first applies horizontal gradient filter followed by thresholding and mathematical morphology operation for preprocessing. The final stage of the preprocessing is the application of connected component analysis in order to estimate the license plate region. For the recognition of the serial numbers of the plates, we developed a very effective algorithm. We call this zerocrossing count algorithm. This paper presents a detail of this algorithm and compare the performance with a template matching algorithm which utilizes correlation coefficient.

• Korean Management Science Review
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• v.19 no.1
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• pp.55-66
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• 2002

Given a directed network, a designated arc, and lowers and upper bounds for the distance of each arc, the preprocessing shortest path problem Is a decision problem that decides whether there is some choice of distance vector such that the distance of each arc honors the given lower and upper bound restriction, and such that the designated arc is on some shortest path from a source node to a destination notre with respect to the chosen distance vector. The preprocessing shortest path problem has many real world applications such as communication and transportation network management and the problem is known to be NP-complete. In this paper, we develop an algorithm that solves the problem using the structural properties of shortest paths.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.22-31
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• 2004

In this paper, the measurements preprocessing algorithm for the fading of bearing and frequency measurements is proposed, which can improve the performance of BFTMA(Bearing and Frequency Target Motion Analysis). The fading and detection relation between bearing and frequency are rigorously established for measurements preprocessing, and BFTMA can be carried out the estimation of target motion by using measurements preprocessing. Batch estimation with bearing and frequency using the proposed algorithm can be applied to estimate the initial target states despite of the fading of frequency measurement. Simulation results show that BFTMA using the proposed measurements preprocessing has superior estimation performance, compared with batch estimation using only bearing measurements.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.4
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• pp.251-258
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• 2005

Automatic document classification may differ significantly according to the characteristics of documents that are subject to classification, as well as classifier's performance. This research identifies e-mail document's characteristics to apply a three-step preprocessing algorithm that can minimize e-mail document's atypical characteristics. In the first 5go, uncertain based sampling algorithm that used Mean Absolute Deviation(MAD), is used to address the question of selection learning document for the rule generation at the time of classification. In the subsequent stage, Weighted vlaue assigning method by attribute is applied to increase the discriminating capability of the terms that appear on the title on the e-mail document characteristic level. in the third and last stage, accuracy level during classification by each category is increased by using Naive Bayesian Presumptive Algorithm's Dynamic Threshold. And, we implemented an E-Mail Recommendtion System using a three-step preprocessing algorithm the enable users for direct and optimal classification with the recommendation of the applicable category when a mail arrives.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1800-1809
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• 1990

This paper proposed a preprocessing algorithm which is named Automatic Tracking Window (ATW), which eliminates the effects of noises at spatial signals and spurious peaks at high-resolution algorithm in bearing estimation algorithm. This method estimates spatial spectrum by periodogram algorisdthm and hihg-resolution algorithm after preprocessing of spatial signal by automatically tracked window.