• The Journal of Korean Association of Computer Education
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• v.6 no.1
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• pp.9-17
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• 2003

XML(eXtensible Markup Language), next generation internet standard language has the advantage of easy re-use and re-structure in other computing environment because it has the separate data, presentation and structure. In this paper, we implement the efficient retrieval system for the general user by limiting the XML documents on the multimedia learning contents for the virtual education system. The system design is based on SCO Metadata unit defined in SCORM as the proposed virtual education standard. Each XML documents has three indexes - keyword, element and attribute. Also, it makes possible to retrieve data without previous knowledge of the DTD by making the element retrieval screen structure for the user interface. And it gives the user various result screen formats such as XML and HTML by restructuring the retrieval result through XML-QL and XSL, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.467-472
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• 2002

In this paper, we propose a Fuzzy Cellular Neural Network(FCNN) that is based on a-Least Trimmed Square Hausdorff distance(a-LTSHD) which applies Hausdorff distance(HD) to the FCNN structure in order to remove the impulse noise of images effectively and also improve the speed of operation. FCNN incorporates Fuzzy set theory to Cellular Neural Network(CNN) structure and HD is used as a scale which computes the distance between set or two pixels in binary images without confrontation of the feature object. This method has been widely used with the adjustment of the object. For performance evaluation, our proposed method is analyzed in comparison with the conventional FCNN, with the Opening-Closing(OC) method, and the LTSHD based FCNN by using Mean Square Error(MSE) and Signal to Noise Ratio(SNR). As a result, the performance of our proposed network structure is found to be superior to the other algorithms in the removal of impulse noise.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.397-400
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• 2011

In this paper, we propose an approach to detect the product label for mobile phone images based on saliency map and the local structure tensor. The object boundary information can be better described by the local structure tensor than other edge detectors, and the saliency map methods can find out the most salient area and shorten the computational time by reducing the size of the orignal image. Therefore, these two methods are considered for our product label detection. The experimental results show an acceptable performance based on our proposed approach.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.283-288
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• 2011

This paper have proposed an object retrieval using the corners area variability based on correlogram. The proposed algorithm is processed as follows. First, the corner points of the object in an image are extracted and then the feature vectors are obtained. It are rearranged according to the number dimension and consist of sequence vectors. And the similarity based on the maximum of sequence vectors is measured. The proposed technique is invariant to the rotation or the transfer of the objects and more efficient in case that the objects present simple structure. In simulation that use Wang's database, the method presents that the recall property is improved by 0.03% and more than the standard corner patch histogram.

• The Mathematical Education
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• v.54 no.4
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• pp.365-383
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• 2015

Factorization asks the recognition of the structure of polynomials, compared to polynomial expansion with process characteristic. Therefore it makes students experience a lot of difficulties. This study aims to figure out causes of the difficulties by identifying students' cognitive characteristics in factorizing in the perspective of 'structure sense'. To do this, we gave six factorizing problems of three types to middle school students and selected six participants as interviewees based on the test results. They were classified into two categories, structure sense and non-structure sense. Through this interview, we figured out the interviewee's cognitive characteristics and the causes of difficulty in the perspective of structure sense. Furthermore, we suggested some didactical implications for encouraging structure sense in factorizing by identifying assistances and obstacles for recognition of structures.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.169-181
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• 2008

Because moving objects usually move on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks such as FNR-tree and MON-tree. But, because FNR-tree and MON-tree are stored by the unit of the moving object's segment, they can't support the whole moving objects' trajectory. In this paper, we propose an efficient trajectory index structure, named Trajectory of Moving objects on Network Tree(TMN Tree), for moving objects. For this, we divide moving object data into spatial and temporal attribute, and preserve moving objects' trajectory. Then, we design index structure which supports not only range query but trajectory query. In addition, we divide user queries into spatio-temporal area based trajectory query, similar-trajectory query, and k-nearest neighbor query. We propose query processing algorithms to support them. Finally, we show that our trajectory index structure outperforms existing tree structures like FNR-Tree and MON-Tree.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.9
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• pp.9-20
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• 2018

There are many large and small spaces in the interior of the building, and these spaces are arranged and connected to form a systematic spatial structure. A structure is a collection of several parts to form a whole. In other words, the spatial structure in architecture can be seen as a whole organized and organized as individual unit spaces are gathered together. Therefore, in order to understand the spatial structure, we first need to define the unit spaces that form part, how they are interconnected and arranged, and then understand how and how these unit spaces are organized to form a whole. The main purpose of this study is to study the structural system of space based on the shape information of space on architectural plane. This means interpreting the process and method of how the unit spaces defined as a certain shape on the architectural plane are organized step by step, integrated into a higher level, and eventually integrated into one whole. In this paper, the shape and layout of the unit space are identified in the architectural plan, the connection relation is defined, and expressed in the network form. And suggests a new methodology for interpreting the organizational process in which the following spaces are integrated as a whole. This new methodology is based on human perceptual characteristics. When people recognize an object, they recognize the object partly and completely. We want to explain the relationship between parts of space and the whole according to their characteristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.800-816
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• 2018

In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.

• Journal of Korea Spatial Information System Society
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• v.8 no.3
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• pp.89-103
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• 2006

Location-Based Services(LBS) has been varied and expanded rapidly in local and overseas markets due to technology developments and expanded applications of wireless internet. Location Based Alert Service(LBA) capable of automatically furnishing data when entering or outing a specific location is expected to become one of the most important services in LBS. For LBA operation, it is essential to periodically get location information about moving object. However, this can cause a serious system load because system should continuously and largely receive location information of many moving objects. Existing and current methods for location polling of moving object are not suitable for an efficient location acquisition and a search structure required for LBA. In this study, to acquire large-scaled location information for LBA, a MDR moving object location polling algorithm will be suggested to reduce unnecessary location information and decrease system load by using mobility patterns of moving object.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.61-75
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• 2008

A script language, which represents and controls avatar behaviors in a natural language style, is especially remarkable, because it can provide a fast and easy way to develop an animation scenario script. However, the studies that consider avatar behavior interactions with various virtual objects and intuitive interface techniques to design scenario script have been lack. Therefore, we proposed a context-based avatar-object behavior model and layered script language. The model defines context-based elements to solve ambiguity problems that occur in abstract behavior interface and it provides user interface to control avatar in the object-based approach. Also, the proposed avatar behavior script language consisted of a layered structure that represents domain user interface, motion sequence, and implement environment information at each level. Using the proposed methods, the user can conveniently and quickly design an avatar-object behavior scenario script.