• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.79-84
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• 2009

This paper explores a method of text watermarking for agglutinative languages and develops a syntactic tree-based syntactic constituent movement scheme. Agglutinative languages provide a good ground for the syntactic tree-based natural language watermarking because syntactic constituent order is relatively free. Our proposed natural language watermarking method consists of seven procedures. First, we construct a syntactic dependency tree of unmarked text. Next, we perform clausal segmentation from the syntactic tree. Third, we choose target syntactic constituents, which will move within its clause. Fourth, we determine the movement direction of the target constituents. Then, we embed a watermark bit for each target constituent. Sixth, if the watermark bit does not coincide with the direction of the target constituent movement, we displace the target constituent in the syntactic tree. Finally, from the modified syntactic tree, we obtain a marked text. From the experimental results, we show that the coverage of our method is 91.53%, and the rate of unnatural sentences of marked text is 23.16%, which is better than that of previous systems. Experimental results also show that the marked text keeps the same style, and it has the same information without semantic distortion.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.3
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• pp.114-127
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• 2010

This study aimed at reviewing the case examples of environmental assessment of development projects within management zones, identifying problems and improvement opportunities and suggesting the direction of environmental assessment for management zones that are increasingly segmented Findings showed that first, the assessment of environment soundness in management zones must incorporate the national land environmental map and wide-area ecological axes established by the Ministry of Environment. Second, regarding development activities in management zones, rather than an issue of simply destroying natural environment in a development site itself during a development period, an issue of permanently isolating ecosystems from surrounding areas in a mid/long-term perspective and continually polluting water in mid-stream/upstream regions where sites are located must be considered. Third, in the case of development projects with vast areas, existing plant communities will be disturbed and the naturalness of vegetation will gradually decline due to foreign tree species introduced for landscape architecture. Therefore, creating buffer forests at forest boundaries and planting native tree species that are same as nearby tree species must be examined. Last but not least, when assessing the environmental soundness of management zones, it would be crucial to comprehensively review the environmental, social and locational features of management zones, including surrounding areas, and set the direction of environmental assessment accordingly.

• Journal of Sensor Science and Technology
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• v.23 no.6
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• pp.377-382
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• 2014

Detecting and segmenting diffuse targets in laser ranging data is a critical problem for tactical reconnaissance. In this study, we propose a new method that facilitates the characterization of diffuse irregularly shaped objects using "spin images," i.e., local 2D histograms of laser returns oriented in 3D space, and a clustering process. The proposed "cluster-based spin imaging" method resolves the problem of using standard spin images for diffuse targets and it eliminates much of the computational complexity that characterizes the production of conventional spin images. The direct processing of pre-segmented laser points, including internal points that penetrate through a diffuse object's topmost surfaces, avoids some of the requirements of the approach used at present for spin image generation, while it also greatly reduces the high computational time overheads incurred by searches to find correlated images. We employed 3D airborne range data over forested terrain to demonstrate the effectiveness of this method in discriminating the different geometric structures of individual tree clusters. Our experiments showed that cluster-based spin images have the potential to separate classes in terms of different ages and portions of tree crowns.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.43-50
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• 2017

In this paper, we are proposing improved vanishing points detection and segments labeling methods for inside wall frame detection from indoor image of a piece of having a colour RGB. A lot of research related to recognizing the frame of artificial structures from the image is being performed due to increase in demand for AR technology. But detect the inside wall frame in indoor images have many objects that caused the occlusion is still a difficult issue. Inner wall frame detection methods are usually segment labeling methods and detect vanishing point methods are used together. In order to improve the vanishing point detection method we proposed using inner wall orthogonality which forms the cube. Also we proposed labeling method using tree based learning and superpixel based segmentation method for labelingthe segments in indoor images. Finally, in experiments have shown improved results about inside wall frame detection according to our methods.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.19-30
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• 2010

It has become important to have some proper guidelines of how to provide public transport information services in response to the rapid IT developments and the wide spread of public information services. The current study takes a contextual approach to the analysis of public transportation information use under a dynamic decision situation, complementing the conventional cross-sectional approaches. Using the CHAID of decision tree induction based on decision table formalism applied to the survey data of activity travel and information use, the study found that the information type and medium choices are strongly affected by the decision contexts in addition to the individuals' socio-demographic characteristics. The results suggest an important implication to the market segmentation of information services for public transportation.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.787-794
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• 2018

The various natural disasters such as floods and localized heavy rains are increasing due to the global warming. If a natural disaster can be detected and analyzed in advance and more effectively, it can prevent enormous damage of natural disasters. Recent development in visual sensor technologies has encouraged various studies on monitoring environments including rivers. In this paper, we propose a method to detect water regions from river images which can be exploited for river surveillance systems using video sensor networks. In the proposed method, we first segment a river image finely using the minimum spanning tree algorithm. Then, the seed regions for the river region and the background region are set by using the preliminary information, and each seed region is expanded by merging similar regions to segment the water region from the image. Experimental results show that the proposed method separates the water region from a river image easier and accurately.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.567-581
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• 2005

Geographical Customer Relationship Management (gCRM) is an integrated solution of Geographic Information System (GIS) and Customer Relationship Management (CRM). In gCRM, GIS is used to show multi-dimensional analytical results of customer information geographically. When customer information is geographically presented, more valuable information appears. In this research we briefly introduce gCRM and show real examples of customer segmentation applied to company.

• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.51-57
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• 2012

Hepatic vessel tree is the key structure for hepatic disease diagnosis and liver surgery planning. Especially, it is used to evaluate the donors' and recipients' liver for the LDLT(Living Donors Liver Transplantation) and estimate the volumes of left and right hepatic lobes for securing their life in the LDLT. In this study, we propose a method to apply canny edge detection that is not affected by noise to the liver images for automatic segmentation of hepatic vessels tree in contrast abdominal MDCT image. Using histograms and average pixel values of the various liver CT images, optimized parameters of the Canny algorithm are determined. It is more time-efficient to use the common parameters than to change parameters manually according to CT images. Candidates of hepatic vessels are extracted by threshold filtering around the detected the vessel edge. Finally, using a system which detects the true-negatives and the false-positives in horizontal and vertical direction, the true-negatives are added in candidate of hepatic vessels and the false-positives are removed. As a result of the process, the various hepatic vessel trees of patients are accurately reconstructed in 3D.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1599-1607
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• 2022

The data mainly used for the model are as follows: the personal information, the information of insurance product, etc. With the data, we suggest three types of models: content-based filtering model, collaborative filtering model and classification models-based model. The content-based filtering model finds the cosine of the angle between the users and items, and recommends items based on the cosine similarity; however, before finding the cosine similarity, we divide into several groups by their features. Segmentation is executed by K-means clustering algorithm and manually operated algorithm. The collaborative filtering model uses interactions that users have with items. The classification models-based model uses decision tree and random forest classifier to recommend items. According to the results of the research, the contents-based filtering model provides the best result. Since the model recommends the item based on the demographic and user features, it indicates that demographic and user features are keys to offer more appropriate items.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4641-4650
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• 2015

This study aims to further strengthen the medical expertise to offer specialized medical care specialization strategies to gain a competitive edge through the customer segmentation of the Regional Public Hospital. Investigation period was selected to study the inpatients 26,658 people January to December 2013. The method of analysis are Cluster analysis and Decision Tree Analysis. In conclusion, female, age over 60, and diseases in musculoskeletal system and connective tissue were commonly selected as identifiers of the target market of Regional Public Hospital. Customers in this target market are loyal to specialized medical service and keeping continuous relationship with these customers through communication and monitoring of results of provided medical service would be important because the effect of word of mouth propagated to other group of customers having equivalent scale of consumption is expected. And the concentration of the scope of medical service of Regional Public Hospital and the collaboration and mutual reliance of medical service under the strategic alliance with other institutions and private hospitals are also needed.