• Journal of Climate Change Research
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• v.4 no.4
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• pp.385-395
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• 2013

In this paper, we target to develop weather platform and services to use in smart devices which is in real-time mobility environment. The existing TPEG-based navigation service requires a dedicated terminal, DMB communication method, and service scalability, so there are limits. In this paper, we analyze, processing and storage the real-time weather information suitable for navigation on the end user's smart devices by weather information service platform has been developed that can provide a standardized. In addition, we develop weavigation services and API for the developer to develop weather services easily. And we introduce system for serving information of dangerous district forecast based on natural disaster dangerous district data.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.510-516
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• 2008

In ubiquitous environment, there are no limits to utilize networks whenever and wherever you are. That pervasive networks are combined with the information devices and then create various services such as car navigation of LBS(location based service) and DMB(Digital Multimedia Broadcasting). As these kinds of services are getting more various, the complexity is also getting higher and ultimately the convergence will make people feel frustrated. One of the solutions is Context-Awareness[1] technology. User interface with context-awareness filters unnecessary information and prevents users from being blocked due to the massive information. In this paper, we describe the seamless service system based on location-awareness, which is a type of context-awareness. We developed the system based on UPnP AV Framework. This system provides the automatic terminal device selection for the nomadic user. The system establishes new connections for the ongoing streaming playback session with the new AV devices without substantial loss of playback so that the user can enjoy the seamless service. The AV device selection based on the user's location needs no user's intervention or notification so it achieves the improvement of usability and complexity.

• Journal of Korean Port Research
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• v.3 no.1
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• pp.3-33
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• 1989

The amount of the Korean export & import in 1987 reached $88.3 billion which was 1.75% of the total world trade and the proportion of foreign dependence to G.N.P was 74.5%. From these facts, we can infer that the development of national economy is largely dependent upon trade. Therefore the role of transportation, especially Ocean transportation, as a basis of economic development through trade is one of the main factors that can not be passed over. Here, We can define that a port as a subsystem of transportation determines the efficiency of the total transportation system. Thus, the purpose of this paper is to contribute in improvement of the efficiency in port, reinforcement of the international competitiveness for exporting goods by the analysis of the cargo handling charges. In order to do this, this paper deals the case of B.C.T.O.C. Furthermore, this study gives some important informations related to the level of tariffs for establishing an autonomous port administration. The Summary of the conclusions of this paper is as follows ; 1) The object of port administration in Korea has been emphasized on the maximization of efficiency in using the port facilities. Nowadays, however, it should be moved to a direction that port is operated under the compound aims considering the public interests and economy. 2) For a criterian of tariff calculation, A tariff system based on the cost accounting is desirable. In general it is recommended that the cost for construction, management, and operation of port is compensated by the revenue from port operation. Therefore, it is necessary for the administration bodies of each port to establish a tariff system on the basis of the independent profit system. 3) For the investigation of actors of tariff adjustment by the Break-even point analysis, (1) When we conducted the B.E.P analysis using total cost as cost term, we got 3.8% discount in tariff at 12% of target profit rate and 1.5% discount at 15% of rate. when we set the target profit rate as 17% we could have the proper tariff level. (2) When using operating cost as cost term, we got 13.1% discount in tariff at 12% of target profit rate and 10.9% discount at 15% of rate. When setting the target profit rat as 28%, we could have the proper tariff level. 4) Comparing with the tariffs of foreign ports for the basic terminal rate, The tariff level of B.C.T.O.C showed 33% of stevedoring charge and 80% of marshalling charge incurred at Kobe port. The comparison with Singapore port gave 50% of transhipment charge and 17% - 20 % of stevedoring charge. 5) We found that the financial structure of B.C.T.O.C was better than those of other companies and the worth fixed assets ratio was too low. The fact of low worth fixed assets ratio implies that the cargo handling facilities should be increased. Moreover, The return of assets for B.T.T.O.C was good but non-operating expenses were still contained too much in. Therefore, we think that it is necessary for B.C.T.O.C. to rationalize business management. Although the present cargo handing charge for B.C.T.O.C is a proper level in terms of a public corporation, for the final recommendation in connection to the results, It is required to take the rationalization process for business management.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.391-393
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• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.