• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.131-137
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• 2017

In the present study, we developed the 4D CT data generation program from CAD-based models. To evaluate the developed program, a CAD-based respiratory motion phantom was designed using CAD software, and converted into 4D CT dataset, which include 10 phases of 3D CTs. The generated 4D CT dataset was evaluated its effectiveness and accuracy through the implementation in radiation therapy planning system (RTPS). Consequently, the results show that the generated 4D CT dataset can be successfully implemented in RTPS, and targets in all phases of 4D CT dataset were moved well according to the user parameters (10 mm) with its stationarily volume (8.8 cc). The developed program, unlike real 4D CT scanner, due to the its ability to make a gold-standard dataset without any artifacts constructed by modality's movements, we believe that this program will be used when the motion effect is important, such as 4D radiation treatment planning and 4D radiation imaging.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.73-83
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• 2009

In this paper we propose an object similarity matching method based on shape characteristics of an object in an image. The proposed method extracts edge points from edges of objects and generates a log polar histogram with respect to each edge point to represent the relative placement of extracted points. It performs the matching in such a way that it compares polar histograms of two edge points sequentially along with edges of objects, and uses a well-known k-NN(nearest neighbor) approach to retrieve similar objects from a database. To verify the proposed method, we've compared it to an existing Shape-Context method. Experimental results reveal that our method is more accurate in object matching than the existing method, showing that when k=5, the precision of our method is 0.75-0.90 while that of the existing one is 0.37, and when k=10, the precision of our method is 0.61-0.80 while that of the existing one is 0.31. In the experiment of rotational transformation, our method is also more robust compared to the existing one, showing that the precision of our method is 0.69 while that of the existing one is 0.30.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.42-52
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• 2002

Information extraction(IE) is a process of recognizing and fetching particular information fragments from a document. In previous work, most IE systems generate the extraction rules called the wrappers manually, and although this manual wrapper generation may achieve more correct extraction, it reveals some problems in flexibility, extensibility, and efficiency. Some other researches that employ automatic ways of generating wrappers are also experiencing difficulties in acquiring and representing useful domain knowledge and in coping with the structural heterogeneity among different information sources, and as a result, the real-world information sources with complex document structures could not be correctly analyzed. In order to resolve these problems, this paper presents an agent-based information extraction system named XTROS that exploits the domain knowledge to learn from documents in a semi-structured information source. This system generates a wrapper for each information source automatically and performs information extraction and information integration by applying this wrapper to the corresponding source. In XTROS, both the domain knowledge and the wrapper are represented as XML-type documents. The wrapper generation algorithm first recognizes the meaning of each logical line of a sample document by using the domain knowledge, and then finds the most frequent pattern from the sequence of semantic representations of the logical lines. Eventually, the location and the structure of this pattern represented by an XML document becomes the wrapper. By testing XTROS on several real-estate information sites, we claim that it creates the correct wrappers for most Web sources and consequently facilitates effective information extraction and integration for heterogeneous and complex information sources.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.119-128
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• 2019

This study aims to analyze the research trends on Smart City and to present implications to policy maker, industry professional, and researcher. Cities around globe have undergone the rapid progress in urbanization and the consequent dramatic increase in urban dwellings over the past few decades, and faced many urban problems in such areas as transportation, environment and housing. Cities around the globe are in a hurry to introduce Smart City to pursue a common goal of solving these urban problems and improving the quality of their lives. However, various conceptual approaches to smart city are causing uncertainty in setting policy goals and establishing direction for implementation. The study collected 11,527 papers titled "Smart City(cities)" from the Scopus DB and Springer DB, and then analyze research status, topic, trends based on abstracts and publication date(year) information using the LDA based Topic Modeling approaches. Research topics are classified into three categories(Services, Technologies, and User Perspective) and eight regarding topics. Out of eight topics, citizen-driven innovation is the most frequently referred. Additional topic network analysis reveals that data and privacy/security are the most prevailing topics affecting others. This study is expected to helps understand the trends of Smart City researches and predict the future researches.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.29-35
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• 2023

CCTV is used for various purposes such as crime prevention, public safety reinforcement, and traffic management. However, as the range and resolution of the camera improve, there is a risk of exposing personal information in the video. Therefore, there is a need for new technologies that can identify individuals while protecting personal information in images. In this paper, we propose histogram-based singular value decomposition for object identification and tracking. The proposed method distinguishes different objects present in the image using color information of the object. For object recognition, YOLO and DeepSORT are used to detect and extract people present in the image. Color values are extracted with a black-and-white histogram using location information of the detected person. Singular value decomposition is used to extract and use only meaningful information among the extracted color values. When using singular value decomposition, the accuracy of object color extraction is increased by using the average of the upper singular value in the result. Color information extracted using singular value decomposition is compared with colors present in other images, and the same person present in different images is detected. Euclidean distance is used for color information comparison, and Top-N is used for accuracy evaluation. As a result of the evaluation, when detecting the same person using a black-and-white histogram and singular value decomposition, it recorded a maximum of 100% to a minimum of 74%.

• Management & Information Systems Review
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• v.30 no.4
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• pp.293-314
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• 2011

The current study investigated the position of future strategy analyzed from the perspective of design management in relation to 10 strategic industries implemented through 3 steps based on promising growth and advancement of Busan industries and evidence provided from a study on the development program of design industry in Busan. It elucidated the role of design industry as a key role from the perspective of design management in an age of creative revolution of futures values. It analyzed the associations between composition of future strategy and design industry in 10 strategic industries of Busan, and explained the relationships with the strategic industries. The perspective of design management involves that design as a ground of values is an industry of the future values, which performs a key strategic function and role, and a theoretical investigation examined the relationships between main functions of design management and business management. Chapter 3 organized items proposed in the design development program in Busan and examined goals and systems which become basic formation of establishment of design strategy in Busan and conditions for design industry in the associations with strategic industry. Chapter 4 described priorities of practicability by step through analyzing and grouping top 30 projects in Busan industry including meanings as key strategy, position relations, and policy priorities by analyzing elements of design management of strategic industry and describing and analyzing the concept of promoting Busan design. The theme of the present study is to change perception of design management as a key value and a condition to decide creativity industry into future industry and to evaluate vision of Busan design industry and meanings proposed as proceeding strategy. The early 21st century is an age when agrarian society has changed into industrial society is dominated by knowledge economy of the information revolution and one should prepare for the growth phase of creative innovation based on creative revolution of the 4th wave of creative society by design management which has become a center in 2000s on the whole. With the advent of creative paradigm and based on the function and role of the current creative economy age new innovation DNA of design management will be created. Design process has changed through information and knowledge-oriented trends of digital through convergence between industries from industrial design to convergence of industries, and it is expected that integrated design of value creation using information and technology will play a key role in Busan design industry development and top 10 strategic industries.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.28-35
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• 2006

Statistical models of shape variability based on active shape models (ASMs) have been successfully utilized to perform segmentation and recognition tasks in two-dimensional (2D) images. Three-dimensional (3D) model-based approaches are more promising than 2D approaches since they can bring in more realistic shape constraints for recognizing and delineating the object boundary. For 3D model-based approaches, however, building the 3D shape model from a training set of segmented instances of an object is a major challenge and currently it remains an open problem in building the 3D shape model, one essential step is to generate a point distribution model (PDM). Corresponding landmarks must be selected in all1 training shapes for generating PDM, and manual determination of landmark correspondences is very time-consuming, tedious, and error-prone. In this paper, we propose a novel automatic method for generating 3D statistical shape models. Given a set of training 3D shapes, we generate a 3D model by 1) building the mean shape fro]n the distance transform of the training shapes, 2) utilizing a tetrahedron method for automatically selecting landmarks on the mean shape, and 3) subsequently propagating these landmarks to each training shape via a distance labeling method. In this paper, we investigate the accuracy and compactness of the 3D model for the human liver built from 50 segmented individual CT data sets. The proposed method is very general without such assumptions and can be applied to other data sets.

• Journal of The Korean Association For Science Education
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• v.34 no.8
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• pp.703-718
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• 2014

This study sought to investigate learning progressions for astronomical systems which synthesized the motion and structure of Earth, Earth-Moon system, solar system, and the universe. For this purpose we developed ordered multiple-choice items, applied them to elementary and middle school students, and provided validity evidence based on the consequence of assessment for interpretation of learning progressions. The study was conducted according to construct modeling approach. The results showed that the OMCs were appropriate for investigating learning progressions on astronomical systems, i.e., based on item fit analysis, students' responses to items were consistent with the measurement of Rasch model. Wright map analysis also represented that the assessment items were very effective in examining students' hypothetical pathways of development of understanding astronomical systems. At the lower anchor of the learning progression, while students perceived the change of location and direction of celestial bodies with only two-dimensional earth-based view, they failed to connect the locations of celestial bodies with Earth-Moon system model, and they could recognized simple patterns of planets in the solar system and milky way. At the intermediate levels, students interpreted celestial motion using the model of Earth rotation and revolution, Earth-Moon system, and solar system with space-based view, and they could also relate the elements of astronomical structures with the models. At the upper anchor, students showed the perspective change between space-based view and earth-based view, and applied it to celestial motion of astronomical systems, and they understood the correlation among sub-elements of astronomical systems and applied it to the system model.