• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.527-534
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• 2011

This paper describes an analysis of topographical changes to the Eulsuk-Island at the Nakdong River Estuary using a long-term dataset of high resolution aerial images from 1983 to 2007. Ground control surveying was performed at some feature points using GPS(Global Positioning System) to accomplish AT(Aerial Triangulation) for past aerial images. Even if some still existing feature points appeared on old aerial images were used as GCPs(Ground Control Points) for past aerial images in AT, its accuracy reached at 1m level. Since then, a quantitative analysis of topographical changes was conducted on digital orthophotos produced by a series of aerial images taken by different years. The change volume of total area, construction, vegetation, buildings and roads could be extracted per each period in study area. The total area decreased from 1983 to 1992, but it has not almost changed since 1992. According to the continuous development, the area of vegetation has steadily decreased, while that of buildings and roads has generally increased. The result of this study can provide us with invaluable base data for further topographical change monitoring in Eulsuk-Island and Nakdong River estuary caused by continuous development in this area.

• International Commerce and Information Review
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• v.16 no.1
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• pp.25-42
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• 2014

Since the reform and opening up in 1978, Chinese economy has been increasing rapidly with a high growth rate, but after 2012 the growth rate decreased as the reform of economic system. While economy in Africa began booming since 2000. Influenced by Global Financial Crisis and European Debt Crisis, economy in Africa slightly slowed down, but it was rebounding apparently from 2010. The urgent demand for energy and the sharp increasing in foreign exchange reserve pushes China to seek overseas markets. As Africa keeps a well relationship with China and the complementarity between China and Africa economy, Africa becomes one of the target markets for China's foreign development. Recently more and more enterprises begin to invest in Africa market. But till now the study on Africa mainly focuses on theoretical research based on real cases, and empirical research are very few and need to be increased. This thesis studies the influence of enterprise feature; local market feature and investment in foreign market on the result satisfaction of Chinese enterprises that invest in Africa markets. At the same time this thesis also studies and analyzes the market access strategy and marketing strategy for Chinese enterprises after entering overseas markets and put forward effective recommendation and suggestion for these enterprises. In order to proceed this study, 317 Chinese enterprises which invest in Africa have been investigated by me. And frequency analysis, reliability analysis, factor analysis, and simple regression analysis have also been conducted by SPSS18.0 APP to verify the hypothesis. The study result suggests that onlu investment in foreign market affects the Performance satisfaction of Chinese enterprises. And the market access strategy and marketing strategy play a role of the mediational effects when Chinese enterprises are investing in Africa.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.187-195
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• 2013

Most of former studies for car license plate detection restrict the image acquisition environment. The aim of this research is to diminish the restrictions by proposing a new method of using SIFT and neural network. SIFT can be used in diverse situations with less restriction because it provides size- and rotation-invariance and large discriminating power. SIFT extracted from the license plate image is divided into the internal(inside class) and the external(outside class) ones and the classifier is trained using them. In the proposed method, by just putting the various types of license plates, the trained neural network classifier can process all of the types. Although the classification performance is not high, the inside class appears densely over the plate region and sparsely over the non-plate regions. These characteristics create a local feature map, from which we can identify the location with the global maximum value as a candidate of license plate region. We collected image database with much less restriction than the conventional researches. The experiment and evaluation were done using this database. In terms of classification accuracy of SIFT keypoints, the correct recognition rate was 97.1%. The precision rate was 62.0% and recall rate was 50.2%. In terms of license plate detection rate, the correct recognition rate was 98.6%.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.63-70
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• 2014

Process of recognizing objects in binary images consists of image segmentation and pattern matching. If binary objects in the image are assumed to be separated, global features such as area, length of perimeter, or the ratio of the two can be used to recognize the objects in the image. However, if such an assumption is not valid, the global features can not be used but local features such as points or line segments should be used to recognize the objects. In this paper points with large curvature along the perimeter are chosen to be the feature points, and pairs of points selected from them are used as local features. Similarity of two local features are defined using elastic deformation energy for making the lengths and angles between gradient vectors at the end points same. Neighbour support value is defined and used for robust recognition of partially occluded binary objects. An experiment on Kimia-25 data showed that the proposed algorithm runs 4.5 times faster than the maximum clique algorithm with same recognition rate.

• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.24-32
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• 2015

The global success of PSY's Gangnam Style was mediated through combination of YouTube and SNS. PSY's success led into some communication scholars' consideration of new international circulation of Korean pop culture (Korean Trend 2.0). In terms of global circulation of pop culture, it is noticeable how users appropriate YouTube channel beyond mere watching music videos and mere international circulation of Korean pop culture. The mode of fan's activity and appropriation contributes to the expansion of the width and amplification of the volume of Korean popular culture as well. The circulation of pop culture was considered in the level of exchange of tangible commodities such as CD, DVD, and so on until the adoption of digital media and Internet. YouTube has brought new mode in which the international circulation of pop culture is mediated without exchange of tangible commodities but was amplified with the diffusion of network. This study grasps how the mode of users' appropriation contributes to international circulation of pop culture through case studies of some K-pop music videos and international K-pop fans' tribute activities. In terms of theoretical perspective, fandom studies will be examined. In terms of research method, the researcher adopts netnography, a participatory observation on network, to find the feature of fandom and its contribution to the international circulation of pop cultures.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.502-508
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• 2015

Stereo images have an advantage of calculating depth(distance) values which can not analyze from 2-D images. However, depth information obtained by stereo images has due to following reasons: it can be obtained by computation process; mismatching occurs when stereo matching is processing in occlusion which has an effect on accuracy of calculating depth information. Also, if global method is used for stereo matching, it needs a lot of computation. Therefore, this paper proposes the method obtaining disparity map which can reduce computation time and has higher accuracy than established method. Edge extraction which is image segmentation based on feature is used for improving accuracy and reducing computation time. Color K-Means method which is image segmentation based on color estimates correlation of objects in an image. And it extracts region of interest for applying Loopy Belief Propagation(LBP). For this, disparity map can be compensated by considering correlation of objects in the image. And it can reduce computation time because of calculating region of interest not all pixels. As a result, disparity map has more accurate and the proposed method reduces computation time.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.3
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• pp.217-232
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• 2019

It was turned out by shrimp beam trawl monthly survey from March, 2015 to February, 2016 that different species composition and abundance of the fish assemblages in Sacheon Bay and coastal waters off Namhae, Korea were compared. As a result of monthly measured sea temperature and salinity of Sacheon Bay and coastal waters off Namhae, sea temperature of both areas was changed seasonally; however, differences in sea temperature occurred during certain periods depending on the region. Salinity was generally low in Sacheon Bay affected by fresh water, and both areas was low in summer and high in winter. A total of 73 species representing 37 families were collected in Sacheon Bay. The dominant fish species in terms of numbers and biomass were Liparis tanakae, $23,077inds./km^2$, $332.1kg/km^2$. A total of 91 fish species representing 49 families were collected in coastal waters off Namhae. The dominant fish species in terms of numbers were Leiognathus nuchalis, $139,683inds./km^2$ and biomass were Chelidonichthys spinosus, $1,078.6kg/km^2$. Analysis of dendrogram of the clustering showed that Sacheon Bay and coastal waters off Namhae were distinctive featured (global R = 0.691, p = 0.017). And except of summer season (July-October), there was a distinctive feature seasonally (global R = 0.844, p = 0.001). The fish species that appeared in common in both areas, where fish species caught in Sacheon Bay, an important inner bay,were smaller than those caught in coastal waters off Namhae appeared. It presented that Sacheon Bay plays a more important role in spawning and nursery ground for fisheries resource than coastal waters off Namhae, Korea.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.