• The Journal of Industrial Distribution & Business
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• v.11 no.10
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• pp.75-89
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• 2020

Purpose: The container terminal is an area that plays an important role in the country's import and export. As the volume of containers increased worldwide, competition between terminals became fiercer, and increasing the productivity of terminals became more important. Re-handling is a serious obstacle that lowers the productivity of terminal. There are two ways to reduce re-handling in the terminal yard. The first method is to load containers in terminal yards using effective carry-in algorithms that reduce re-handling. The second method is to carry out effective remarshalling. In this paper, the performance of various carry-in algorithms and various remarshalling algorithms are reviewed. Next, we try to find the most effective combination of carry-in algorithm and remarshalling algorithm. Research design, data and methodology: In this paper, we analyze the performance of the four carry-in algorithms, AP, MDF, LVF, RP and the four remarshalling algorithms, ASI, ASI+, ASO, ASO+. And after making all the combinations of carry-in algorithms and remarshalling algorithms, we compare their performance to find the best combination. To that end, many experiments are conducted with eight types of 100 bays through simulation. Results: The results of experiments showed that AP was effective among the carry-in algorithms and ASO+ was effective among remarshalling algorithms. In the case of the LVF algorithm, the effect of carrying in was bad, but it was found to be effective in finding remarshalling solution. And we could see that ASI+ and ASO+, algorithms that carry out remarshalling even if they fail to find remarshalling solution, are also more effective than ASI and ASO. And among the combinations of carry-in algorithms and remarshalling algorithms, we could see that the combination of AP algorithm and ASO+ algorithm was the most effective combination. Conclusion: We compared the performance of the carry-in algorithms and the remarshalling algorithms and the performance of their combination. Since the performance of the container yard has a significant effect on the performance of the entire container terminal, it is believed that the results of this experiment will be effective in improving the performance of the container terminal when carrying-in or when remarshalling.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.673-685
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• 2018

Procrustes analysis is a useful technique useful to measure, compare shape differences and estimate a mean shape for objects; however it is based on a least squares criterion and is affected by some outliers. Therefore, we propose two generalized Procrustes analysis methods based on M-estimation and least median of squares estimation that are resistant to object outliers. In addition, two algorithms are given for practical implementation. A simulation study and some examples are used to examine and compared the performances of the algorithms with the least square method. Moreover since these resistant GPA methods are available for higher dimensions, we need some methods to visualize the objects and mean shape effectively. Also since we have concentrated on resistant fitting methods without considering shape distributions, we wish to shape analysis not be sensitive to particular model.

• Electronics and Telecommunications Trends
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• v.4 no.1
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• pp.93-117
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• 1989

Computational Geometry is concerned with the design and analysis of computational algorithms which solve geometry problems. Geometry problems have a large number of applications areas such as pattern recognition, image processing, computer graphics, VLSI design and statistics since they involve inherently geometric problems for which efficient algorithms have to be developed. Several parallel algorithms, based on various parallel computation models, have been proposed for solving geometric problems. We review the current status of the parallel algorithms in computational geometry.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1013-1020
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• 2013

In this paper the super-resolution time delay estimation algorithms based on eigen-analysis are developed for spread spectrum signals along with their comparative performance analysis. First, we shall develop super-resolution time delay estimation algorithms using the representative eigen-analysis based AOA (angle-of-arrival) estimation algorithms such as MUSIC, Minimum-Norm, and ESPRIT, and apply them to the ISO/IEC 24730-2.1 real-time locating system (RTLS) employing a direct sequence spread spectrum (DS-SS) technique to compare their performances in RTLS environments. Simulation results illustrate that all the three algorithms can resolve multipath signals whose delay differences are even smaller than the Rayleigh resolution limit. Simulation results also show that MUSIC and Minimum-Norm provide a similar performance while ESPRIT is inferior to both algorithms in RTLS environments.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.281-287
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• 2003

This paper proposed an improvement scheme for effective usage of radio-frequency management system(RFMS), which has been operated to facilitate national spectrum management and monitoring in Korea. Based on the wave propagation models, interference analysis algorithms, and sharing criteria recommended by ITU-R, we derived criteria for the automated selection of the channel interference analysis algorithms and sharing conditions adequate to the environment to be analysed. Then using the obtained criteria, computer and program has been made and shown to select the most appropriate propagation models, interference analysis algorithms, and sharing criteria from the ones provided in RFMS, with the illustrative example.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.241-247
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• 2021

Particulate matter has emerged as a serious global problem, necessitating highly reliable information on the matter. Therefore, various algorithms have been used in studies to predict particulate matter. In this study, we compared the prediction performance of neural network models that have been actively studied for particulate matter prediction. Among the neural network algorithms, a deep neural network (DNN), a recurrent neural network, and long short-term memory were used to design the optimal prediction model using a hyper-parameter search. In the comparative analysis of the prediction performance of each model, the DNN model showed a lower root mean square error (RMSE) than the other algorithms in the performance comparison using the RMSE and the level of accuracy as metrics for evaluation. The stability of the recurrent neural network was slightly lower than that of the other algorithms, although the accuracy was higher.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.295-301
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• 2018

This study compares optimization algorithms for efficient estimations of ship's hydrodynamic coefficients. Two constrained algorithms, the interior point and the sequential quadratic programming, are compared for the estimation. Mathematical optimization is designed to get optimal hydrodynamic coefficients for modelling a ship, and benchmark data are collected from sea trials of a training ship. A calibration for environmental influence and a sensitivity analysis for efficiency are carried out prior to implementing the optimization. The optimization is composed of three steps considering correlation between coefficients and manoeuvre characteristics. Manoeuvre characteristics of simulation results for both sets of optimized coefficients are close to each other, and they are also fit to the benchmark data. However, this similarity interferes with the comparison, and it is supposed that optimization conditions, such as designed variables and constraints, are not sufficient to compare them strictly. An enhanced optimization with additional sea trial measurement data should be carried out in future studies.

• Proceedings of the KSRS Conference
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• v.1
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• pp.516-519
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• 2006

Military targets in SAR images are not distinguished easily unlike those in optical images, because targets are only dozens of pixels and they have many corner reflectors sensitive to the incidence angle of radar signals. Due to those problems, SAR image analysts have difficulties in recognizing military targets captured by SAR images. Furthermore, manual analysis cannot respond promptly enough to rapidly changing situations such as battle field. We need automated analysis to solve these problems. In this paper, we analyzed algorithms for prescreening of military targets in SAR images. We implemented some prescreening algorithms and tested the algorithms using SAR data. As a result, we will report performance of the tested prescreening algorithms.

• Journal of The Korean Association For Science Education
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• v.7 no.2
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• pp.37-43
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• 1987

Computer in one of the most tremendous achievements of the modern scientific technique. Not only in government, business, research and education but in our daily life. computers are widely utilized to assist in solving various problems. With increasing frequency, it is recognized that a right understanding of the computer is necessary: naturally, this recognition places a great emphasis on the computer education. In Korea computer is chosen either as an optional subject or as a kind of group activity in many schools. It is the purpose of this study to compare and analyze the internal sorting algorithms which are used frequently in data processing. and to present the results of program analysis. which will make it possible to choose the appropriate sorting algorithm for each data processing. Generally the algorithms are coded in a language appropriate for structured programming. like PASCAL: however, here the algorithms are expressed in BASIC which is widely used with the personal computers so that the students and the teachers may understand them easily.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.78-85
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• 1996

The set of admissible time-variations in the input signal can be separated into two categories : slow parameter changes and large parameter changes which occur infrequently. A common approach used in the tracking of slowly time-varying parameters is the exponential recursive least-squares(RLS) algorithm. There have been a variety of research works on the error analysis of the exponential RLS algorithm for the slowly time-varying parameters. In this paper, the focus has been given to the error analysis of exponential RLS algorithms for the input data with abrupt property changes. The voiced speech signal is chosen as the principal application. In order to analyze the error performance of the exponential RLS algorithm, deterministic properties of the exponential RLS algorithms is first analyzed for the case of abrupt parameter changes, the impulsive input(or error variance) synchronous to the abrupt change of parameter vectors actually enhances the convergence of the exponential RLS algorithm. The analysis has also been verified through simulations on the synthetic speech signal.