• Journal of Navigation and Port Research
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• v.31 no.2
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• pp.133-139
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• 2007

Relative importance of maritime transport that takes charge of main current of freight in country' economy is very large. Especially, port and facility carry out important role which treats freight of import and export smoothly and improves international trade as turning point, to achieve key role on connection and association between sea and land. For such reason, enlargement of port facilities or development of port needs to grasp exactly the utilization of port, attributes and selective factors of shipper. On the other hand, the amounts of physical distribution on Mokpo port located in Korean west coast are increasing, with fast economic growth of East Asian including China. This study uses discrete choice model that is measuring to analyze attribute and characteristic of Mokpo port, and analyzes port selection by decision factors of shipper. This paper composed a questionnaire using the result of preceding research, to decide port selection factor among competitive ports. Through factor analysis on a basis of the questionnaire' result, five principal components were extracted. These are resorted out by Logit model, to grasp competitive elements of port. This research fin present direction which raises competitive power of ports in west coast of Korea, especially on alternative and concentration of middle-class port as Mokpo may be useful.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.35-35
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• 2012

Most grid-based distributed hydrologic models are complex in terms of data requirements, parameter estimation and computational demand. To address these issues, a simple grid-based hydrologic model is developed in a geographic information system (GIS) environment using storage-release concept. The model is named GIS Storage Release Model (GIS-StoRM). The storage-release concept uses the travel time within each cell to compute howmuch water is stored or released to the watershed outlet at each time step. The travel time within each cell is computed by combining the kinematic wave equation with Manning's equation. The input to GIS-StoRM includes geospatial datasets such as radar rainfall data (NEXRAD), land use and digital elevation model (DEM). The structural framework for GIS-StoRM is developed by exploiting geographic features in GIS as hydrologic modeling objects, which store and process geospatial and temporal information for hydrologic modeling. Hydrologic modeling objects developed in this study handle time series, raster and vector data within GIS to: (i) exchange input-output between modeling objects, (ii) extract parameters from GIS data; and (iii) simulate hydrologic processes. Conceptual and structural framework of GIS StoRM including its application to Pleasant Creek watershed in Indiana will be presented.

• Korean Journal of Hydrosciences
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• v.7
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• pp.21-35
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• 1996

This Study is to develop the suitable hydrologic models for determination of the size and location of detention storage facilities to restrain stormwater runoff in urban areas. Hypothetical areas of two levels are considered to seize the hydrologic response characteristics. A one-square-kilometer ares is selected for the catchment level, and a 10-square-kilometer area consisting of 10 catchments is adapted at the watershed level as representative of urban drainage area. In this analysis, different rainfall freqyencies, land uses, drainage patte군, basin shates and detention storage policies are considered. Folw reduction effect of detention storage facilities is deduced from storage ratio and detention basin factor. A substantial saving in detention storage volumes is achieved 노두 the detention storage is planned at the watershed level rather than the catchment level. For the application of real watersheds, two watersheds in Seoul metropolitan area-Jamshil 2 and Seongnae 1-are selected on the basis of hydrologic response charactaristics. Through the regression analysis between dimensionless deterntion storage volume, dimensionless upstream area ratio and reduction rate of storage ratio, the regression equations to determine the size and location of detention storage faclities are presented.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.34-37
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• 2019

The drone uses a Microwave Doppler Radar Sensor which operates at 10.525GHz to recognize harmful animal which intruded into the arable land. Moreover provide user with notification services on risk factors. Subsequently, the user the drone's camera and a camera-only app to watch the farmland in real-time, steer the drone directly, and use the NeoPixel LED ring and the speaker to stimulate the harmful animal's sight and hearing to induce escape.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.303-314
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• 2019

Indonesia's most eastern provinces enjoy special autonomy status but still suffer from the highest poverty level in the entire nation. Using the Williamson index to test the Simon Kuznets theory, this study examines development equality at pre-and post-special autonomy in the provinces of Papua and West Papua. It uses gross domestic products per capita and population from 29 regencies/cities in Papua and 13 regencies/cities in West Papua to measure the Williamson index in addition to in-depth interviews with legislative members and document analysis to validate the findings. The study found that the regional development gap before special autonomy is relatively smaller than that existing after special autonomy. The Kuznets' curve is not proven in the special autonomy era, meaning that the imposition of autonomy status has led to the creation of a higher development gap in these provinces. Although the special autonomy status has prompted an increased opportunity for political participation by the indigenous people, greater challenges are posed by the lack of human resources, poor government administration, difficult geographical access and the issue of land acquisition. Continuous development initiatives followed up with adequate supervision, greater transparency and law enforcement from government bureaucrats and legislatures are recommended to reduce the inequality.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.327-338
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• 2000

The forest conditions of North Korea has been a great concern since it was known to be closely related to many environmental problems of the disastrous flooding, soil erosion, and food shortage. To assess the long-term changes of forest area as well as the canopy conditions, several sources of multitemporal satellite data were applied to the study area near Kaesung. KOMPSAT-1 EOC data were overlaid with 1981 topographic map showing the boundaries of forest to assess the deforestation area. Delineation of the cleared forest was performed by both visual interpretation and unsupervised classification. For analyzing the change of forest canopy condition, multiple scenes of Landsat and SPOT data were selected. After preprocessing of the multitemporal satellite data, such as image registration and normalization, the normalized difference vegetation index (NDVI) was derived as a representation of forest canopy conditions. Although the panchromatic EOC data had radiometric limitation to classify diverse cover types, they can be effectively used t detect and delineate the deforested area. The results showed that a large portion of forest land has been cleared for the urban and agricultural uses during the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. Possible causes of the deforestation and the temporal pattern of canopy conditions are discussed.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.479-490
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• 2003

This study proposed a modified anisotropic diffusion restoration for image classification. The anisotropic diffusion restoration uses a probabilistic model based on Markov random field, which represents geographical connectedness existing in many remotely sensed images, and restores them through an iterative diffusion processing. In every iteration, the bonding-strength coefficient associated with the spatial connectedness is adaptively estimated as a function of brightness gradient. The gradient function involves a constant called "temperature", which determines the amount of discontinuity and is continuously decreased in the iterations. In this study, the proposed method has been extensively evaluated using simulated images that were generated from various patterns. These patterns represent the types of natural and artificial land-use. The simulated images were restored by the modified anisotropic diffusion technique, and then classified by a multistage hierarchical clustering classification. The classification results were compared to them of the non-restored simulation images. The restoration with an appropriate temperature considerably reduces error in classification, especially for noisy images. This study made experiments on the satellite images remotely sensed on the Korean peninsula. The experimental results show that the proposed approach is also very effective on image classification in remote sensing.

• Journal of Korea Planning Association
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• v.53 no.7
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• pp.49-66
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• 2018

The purpose of this study is to analyze neighborhood environmental factors affecting bicycle accidents and accidental severity in Seoul, Korea. The use of bicycles has increased rapidly as daily transportation means in recent years. As a result, bicycle accidents are also steadily increasing. Using Traffic Accident Analysis System (TAAS) data from 2015 to 2017, this study uses negative binomial regression analysis to identify neighborhood environmental factors affecting bicycle accidents and accidential severity. The main results are as follows. First, bicycle accidents are more likely to occur in commercial and mixed land use areas where pedestrians, bicycle and vehicles are moving together. Second, bicycle accidents are positively associated with road structures such as four-way intersection. In contrast, three-way intersection is negatively associated with serious bicycle accidents. The density of speed hump or street tree is negatively associated with bicycle accidents and accidential severity. This finding indicates the effect of speed limit or street trees on bicycle safety. Fourth, bicycle infrastructures are also important factors affecting bicycle accidents and accidential severity. Bicycle-exclusive roads or bicycle-pedestrian mixed roads are positively associated with bicycle accidents and accidential severity. Finally, this study suggests policy implications to improve bicycle safety.

• Journal of Korea Planning Association
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• v.54 no.7
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• pp.5-23
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• 2019

The central government has implemented policies to strengthen the competitiveness of small and medium sized cities for balanced development at the national scale. However, since it is often difficult to enhance the competitiveness through partial projects of each jurisdiction, many local governments collaborate at the regional scale. This suggests that a regional approach is important for the management of small and medium sized cities. On the one hand, the concept of network city suggests that various functional networks can affect the growth of small and medium sized cities. Given this background, the purposes of this study are to delineate regional boundaries at national scale and identify their relations of growth by using functional network and Moran's I index. The study uses the Markov-chain model and cluster analysis to delineate the regions, and Moran's I is employed to identify the relations of growth. The results show that interactions between jurisdictions through networks could be crucial factors for growth of small and medium sized cities, while the networks based on passenger travel and freight movement have different implications. The results suggest that policy makers should not only consider local level investments, but also take the characteristics of networks between cities into account for achieving balanced development and developing regeneration policies.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.406-412
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• 2022

Scene classification of very high-resolution (VHR) imagery can attribute semantics to land cover in a variety of domains. Real-world application requirements have not been addressed by conventional techniques for remote sensing image classification. Recent research has demonstrated that deep convolutional neural networks (CNNs) are effective at extracting features due to their strong feature extraction capabilities. In order to improve classification performance, these approaches rely primarily on semantic information. Since the abstract and global semantic information makes it difficult for the network to correctly classify scene images with similar structures and high interclass similarity, it achieves a low classification accuracy. We propose a VHR remote sensing image classification model that uses extracts the global feature from the original VHR image using an EfficientNet-V2L CNN pre-trained to detect similar classes. The image is then classified using a multilayer perceptron (MLP). This method was evaluated using two benchmark remote sensing datasets: the 21-class UC Merced, and the 38-class PatternNet. As compared to other state-of-the-art models, the proposed model significantly improves performance.