• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.3
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• pp.253-258
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• 2015

The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.85-87
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• 2000

In pattern classification, the Bhattacharyya distance has been used as a class separability measure and provides useful information for feature selection and extraction. In this paper, we propose a method to predict the classification error for multimodal data based on the Bhattacharyya distance. In our approach, we first approximate the pdf of multimodal distribution with a Gaussian mixture model and find the bhattacharyya distance and classification error. Exprimental results showed that there is a strong relationship between the Bhattacharyya distance and the classification error for multimodal data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.147-154
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• 2002

In this paper, we propose an error estimation method based on the Bhattacharyya distance for multimodal data. First, we try to find the empirical relationship between the classification error and the Bhattacharyya distance. Then, we investigate the possibility to derive the error estimation equation based on the Bhattacharyya distance for multimodal data. We assume that the distribution of multimodal data can be approximated as a mixture of several Gaussian distributions. Experimental results with remotely sensed data showed that there exist strong relationships between the Bhattacharyya distance and the classification error and that it is possible to predict the classification error using the Bhattacharyya distance for multimodal data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.265-271
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• 2006

According to globalization of world economy by extension of production, sales and distribution all around the world and international transportation system changed into a transport system that puts great importance on speediness and value-added services, international transport system is changing into a Multimodal Transport Routing centered system that systematically connects marine, air and rail transports. Due to such changes production, sales and distribution must be provided in time and Multimodal Transport Routing, which can provide multi-dimensional logistics services to customers of global network, is needed but information connection for international transport and connection system between transport modes are insufficient and can not be activated. Especially in Korea, selection standard of 3rd party logistics companies and transport companies is presented, but logistics exclusive companies, which plan and execute the transportation, can't present a systematic evaluation standard for international Multimodal Transport Routing, selection. Thus, this research surveys important previous studies about Multimodal Transport Routing, selection, derives an evaluation standard for Multimodal Transport Routing, selection through interview with company officials, and presents a theoretical basis for Multimodal Transport Routing, selection through systematic analysis of Multimodal Transport Routing, selection using Analytical Hierarchy Process (AHP).

• Journal of Korean Society of Transportation
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• v.5 no.1
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• pp.85-99
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• 1987

The transport a administration in Korea is meeting demands of developing international multimodal transport system. In the past, as Korea transport policy has been emphasizing on the passenger traffic, the physical distribution sector is far behind international trend. Regarding the urging necessities of reducting costs in transport in order to upgrade the competitive edge of industries, Korea has to develop the most efficient transport system so called international multimodal transport system. The existing transport system is inefficient because each transport mode is separate, so this system is aiming at reducing cost and time and developing freight transport. The scope and scheme of this thesis should be as following. Chapter 2. Systems Approach of International multimodal transport 1. general systems theory 2. definition of International multimodal transport system 3. MTO (multimodal transport operator) Chapter 3. Current Situation and Problems of this System. 1. international law and practice 2.current situation A. Europe B. U.S. C. Japan D. Korea Chapter 4. Policy Goal for Improving this System Chapter 5. conclusion.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.251-259
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• 2006

The increase in international logistics market and various customer demands emphasize the importance of Multimodal Transportation, and that market is continuously keep growing. In order to ensure competitive superiority in a market of such infinite competition, service that can satisfy each individual customer by considering various customer characteristics, has become an issue. Thus, through the aspect of service, in order to improve customer satisfaction, growing factors of Multimodal Transportation Route on was studied in this research. For this research, first of all main service factors that affect the growth of Multimodal Transportation were seized by literature survey and positive research. The, by using these factors a methodology that enables individual customers to assess Multimodal Transportation Route was studied. Through this research, individual customers can acquire objective assessment data and Multimodal Transportation companies can seize what factors are considered as important by their customers.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.29 no.3
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• pp.386-392
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• 1996

A numerical method based on genetic algorithms was introduced to characterize the grain-size distribution more effectively. This technique was proved significant particularly for multimodal size distributions, as was verified for samples from Korea Strait continental shelf. Sediment samples collected from the Korea Strait continental shelf revealed that $96\%$ of the grain-size distributions were multimodal. Therefore, the use of grain-size parameters was not the ideal method. As an alternative method, the decomposition of sue curves into elementary normal component curves was used. Means and standard deviations of 593 decomposed normal components were calculated by a numerical method from 268 size curves of Korea Strait sediments. The mean values of decomposed normal components showed peaks at $1\~3\phi\;and\;7\~9\phi$ size classes. The plot of mean and standard deviation values of the coarse fraction normal components on the map showed a characteristic areal distribution. The characteristic distribution was found to derive from underlying Pleistocene sediment on the basis of sea bottom geologic distribution of the area. The method of decomposition into normal components was found to be more effective than the analysis using traditional grain-size parameters in investigation of multimodal size distribution of Korea Strait shelf sediment.

• Journal of Distribution Science
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• v.1 no.1
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• pp.39-61
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• 1999

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.637-640
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• 2023

This paper presents multimodal image fusion with human pose for detecting abnormal human behaviors in low illumination conditions. Detecting human behaviors in low illumination conditions is challenging due to its limited visibility of the objects of interest in the scene. Multimodal image fusion simultaneously combines visual information in the visible spectrum and thermal radiation information in the long-wave infrared spectrum. We propose an abnormal event detection scheme based on the multimodal fused image and the human poses using the keypoints to characterize the action of the human body. Our method assumes that human behaviors are well correlated to body keypoints such as shoulders, elbows, wrists, hips. In detail, we extracted the human keypoint coordinates from human targets in multimodal fused videos. The coordinate values are used as inputs to train a multilayer perceptron network to classify human behaviors as normal or abnormal. Our experiment demonstrates a significant result on multimodal imaging dataset. The proposed model can capture the complex distribution pattern for both normal and abnormal behaviors.

• 한국해양학회지
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• v.28 no.2
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• pp.114-120
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• 1993

Numerical method of nonlinear regression was introduced to characterize grain-size distribution more effectively than using the traditional textural parameters. This technique proved critical particularly to multimodal size distributions, as exemplified by samples from Cheju strait continental shelf. Grain-size analysis of samples collected from the Cheju Strait continental shelf reveals that 86% of the grain-size distributions are multimodal. As multimodal grain-size distribution deviates from the statistical (log) normal distribution, the grain-size parameters traditionally used in sediment studies do not describe the distribution efficiently. Therefore, the use of grain-size curves into elementary normal component curves was used. Means and standard deviations of 387 decomposed normal components were decided by a decomposition method (nonlinear least square regression) from 167 size curves of the Cheju Strait sediments. The mean values of decomposed normal components show peaks at 1-3 phi and 8-9 phi size classes. The plot of mean values of the coarse fraction normal components on the map shows a characteristic and complex areal distribution. On the basis of the areal distribution of the mean values of the components and that of isopach of total Plenipotence sediment, the areal distribution of layers composing a transgressive sand of Late Plenipotence age were revealed.