• Journal of Advanced Navigation Technology
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• v.12 no.2
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• pp.109-114
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• 2008

As the Ubiquitous times approach, an interest regarding a Ubiquitous sensor network to be the only during key technology is rising. Currently, The fast development which radio communication technique is creating new services from the industry sector which is various from convenient characteristic and the ease characteristic side. Specially, rise and development of the radio communication technique which is various from environment monitor ring field makes to be improved about sharp curtailment of establishment and logistics relation expense, and collection period of the data which occurs real-time from site, reliability and delivery characteristic. But continuous application and the success about the environment monitor ring field of radio communication technique will be able to trust And It is important to provide time information which is appropriate real-time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1661-1669
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• 2010

In this paper, I propose an Energy efficient Clustering based on Genetic Algorithm(ECGA) which reduces energy consumption by distributing energy overload to cluster group head and cluster head in order to lengthen the lifetime of sensor network. ECGA algorithm calculates the values like estimated energy cost summary, average and standard deviation of residual quantity of sensor node and applies them to fitness function. By using the fitness function, we can obtain the optimum condition of cluster group and cluster. I demonstrated that ECGA algorithm reduces the energy consumption and lengthens the lifetime of network compared with the previous clustering method by stimulation.

• Proceedings of the Safety Management and Science Conference
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• 2008.04a
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• pp.383-387
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• 2008

Nowadays, the tendency of world air cargo is noteworthy and air traffic in terms of cargo throughput will no doubt grow significantly in the new Region, with India and China's booming economy and the upcoming Olympics 2008. For example, in the first 11 months of 2006 cargo traffic was increased by 6.3%. First of all, the market of air cargo in Korea grows very quickly and diversifies. It is an essential factor in the process of development of Northeast-Asia as a hub for Air Cargo logistics. However the process of air cargo in Korea is complex as compared with other north-east asia nations. At the same time, it has many problems and causes inconvenience to owners of freight. This paper investigated the process of air cargo in Korea now and analyzed problems of the process. We emphasize that 4PL is the excellent solution from among many alternatives. It is also worthy of notice that EPCglobal network strengthen the role of 4PL. In conclusion, the 4PL system based on EPCglobal network will result in a good success, so it will raise a prestige of air cargo in Korea to a higher position.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.305-319
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• 2019

The prediction of the sum of container is very important in the field of container transport. Many influencing factors can affect the prediction results. These factors are usually composed of many variables, whose composition is often very complex. In this paper, we use gray relational analysis to set up a proper forecast index system for the prediction of the sum of containers in foreign trade. To address the issue of the low accuracy of the traditional prediction models and the problem of the difficulty of fully considering all the factors and other issues, this paper puts forward a prediction model which is combined with a back-propagation (BP) neural networks and the support vector machine (SVM). First, it gives the prediction with the data normalized by the BP neural network and generates a preliminary forecast data. Second, it employs SVM for the residual correction calculation for the results based on the preliminary data. The results of practical examples show that the overall relative error of the combined prediction model is no more than 1.5%, which is less than the relative error of the single prediction models. It is hoped that the research can provide a useful reference for the prediction of the sum of container and related studies.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.393-399
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• 2022

During the ship hull design process, resistance performance estimation is generally calculated by simulation using computational fluid dynamics. Since such hull resistance performance simulation requires a lot of time and computation resources, the time taken for simulation is reduced by CPU clusters having more than tens of cores in order to complete the hull design within the required deadline of the ship owner. In this paper, we propose a method for estimating resistance performance of ship hull by simulation using a graph neural network. This method converts the 3D geometric information of the hull mesh and the physical quantity of the surface into a mathematical graph, and is implemented as a deep learning model that predicts the future simulation state from the input state. The method proposed in the resistance performance experiment of simple hull showed an average error of about 3.5 % throughout the simulation.

• Korea Trade Review
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• v.47 no.2
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• pp.175-193
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• 2022

This study analyzes the effects of road transportation networks on the local economy in korea. The analysis methods are SNA and spatial panel regression model. The subjects of this study are inland areas of Korea, and the research period is from 2010 to 2019. The network analysis showed that the connection centrality of Gyeongg-do was high internally and externally. Gyeonggi-do has played a central role in the domestic road freight transportation industry. The results of spatial panel regression analysis showed that there was economic competition between regions. Domestic road transportation industry has been competitive among regions and has economic ripple effect. And Internal cargo has been shown to boost the economy of the region. But internal cargo has been shown to lower the economy of surrounding regions, but external cargo has been shown to increase the economy. In order to revitalize the local economy, it is necessary to increase road cargo.

• The Journal of Bigdata
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• v.4 no.2
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• pp.159-173
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• 2019

Last-Mile delivery optimization plays a key role in the urban supply chain operation, which is the most expensive and time-consuming and most complicated part of the whole delivery process. The urban consolidation center (UCC) is regarded as a significant asset for supporting customer demand in the last-mile delivery service. It is the key benefit of UCC to improve the load balance of vehicles and to reduce the total traveling distance by finding the better route with the well-organized multi-leg vehicle journey in the urban area. This paper presents the model using multiple scenario analysis integrated with mathematical optimization techniques using Geographic Information System (GIS). The model aims to find the best solution for the distribution network consisted of DC and UCC, which is applied to the case of Ulaanbaatar Mongolia. The proposed methodology integrates two sub-models, location-allocation model and vehicle routing problem. The multiple scenarios devised by selecting locations of UCC are compared considering the general performance and delivery patterns together. It has been adopted to make better decisions the quantitative metrics such as the economic value of capital cost, operating cost, and balance of using available resources. The result of this research may help the manager or public authorities who should design the distribution network for the last mile delivery service optimization using UCC within the urban area.

• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.29-39
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• 2016

As geopolitical, archaeological and strategic interests on cooperation with countries in the Far Eastern Area is gradually increased, countries are competing to attract or install a logistics or manufacturing hub in their countries. In this study, we investigated the relative importance of factors on the main three and nine detailed criteria from the domestic and overseas experts on Far Eastern Area. Using AHP(Analytic Hierarchy Process) analysis, priority importance of factors was derived. As a result, we find that the most important factor was economic factor. In detail, industrial complex creation was the highest factor and the institutional guarantees for the investment on policy and transportation network was second highest factor. Based on analysis result, specific competitiveness level in the 10 region of Far East was follows. Hunchun, Vladivostok, Yanji, Tumen, Rajin, Hassan, Ussuriysk, Cheongjin, Mihaylov Skiing, Nije Jeuchinski were showed in order. Hunchun showed the highest competitive level in location, topography, compliance to the around cities, transportation network, industrial complex, excellence in logistics facilities, long-term investment plans, institutional guarantees for investment, customs efficiency and political stability. However, in other factors such as population and number of households, public facilities, potential demand and resource utilization, Vladivostok showed the highest level.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.7-16
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• 2019

The purpose of this study is to identify the characteristics of researches that have been conducted for the last 20 years through analyzing global research trends and evolutions of design articles from 1999 to 2018 with keyword network analysis. For this purpose, we selected 3,569 articles in 22 journals related to design research retrieved from the Scopus database and constructed keyword network model through the author keyword and index keyword. The frequency of the author and index keyword, the centrality of betweenness and degree were analyzed with the keyword network. The results show that design has been applied to various fields for recent 20 years, and the research trends of design could be quantitatively characterized by keyword network analysis. The result of this study could be used to suggest future research topics in the field of design based on quantitative and empirical data.

• Spatial Information Research
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• v.20 no.4
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• pp.29-36
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• 2012

The low-carbon freight transportation system was introduced due to increase traffic congestion cost and carbon-dioxide for global climate change according to expanding city logistics demands. It is necessary to create 3D-based road network map for representing realistic road geometry with consideration of fuel consumption and carbon emissions. This study propose that 3D road network model expressed to realistic topography and road structure within trunk road for intercity freight through overlaying 2D-based transport-related thematic map and 1m-resolution DEM. The 3D-based road network map for the experimental road sections(Pyeongtaek harbor-Uiwang IC) was verified by GPS/INS survey and fuel consumption simulation. The results corresponded to effectively reflect realistic road geometry (RMSE=0.87m) except some complex structure such as overpass, and also actual fuel consumption. We expect that Green-based freight route planning and navigation system reflected on 3D geometry of complex road structure will be developed for effectively resolving energy and environmental problems.