• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.92-100
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• 2012

A map of complex environment can be generated using a robot carrying sensors. However, representation of environments directly using the integration of sensor data tells only spatial existence. In order to execute high-level applications, robots need semantic knowledge of the environments. This research investigates the design of a system for recognizing objects in 3D point clouds of urban environments. The proposed system is decomposed into five steps: sequential LIDAR scan, point classification, ground detection and elimination, segmentation, and object classification. This method could classify the various objects in urban environment, such as cars, trees, buildings, posts, etc. The simple methods minimizing time-consuming process are developed to guarantee real-time performance and to perform data classification on-the-fly as data is being acquired. To evaluate performance of the proposed methods, computation time and recognition rate are analyzed. Experimental results demonstrate that the proposed algorithm has efficiency in fast understanding the semantic knowledge of a dynamic urban environment.

• Journal of Korea Multimedia Society
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• v.15 no.8
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• pp.963-976
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• 2012

'Gesture' except for voice is the most intuitive means of communication. Thus, many researches on how to control computer using gesture are in progress. User detection and tracking in these studies is one of the most important processes. Conventional 2D object detection and tracking methods are sensitive to changes in the environment or lights, and a mix of 2D and 3D information methods has the disadvantage of a lot of computational complexity. In addition, using conventional 3D information methods can not segment similar depth object. In this paper, we propose object detection and tracking method using Depth Projection Map that is the cumulative value of the depth and motion information. Simulation results show that our method is robust to changes in lighting or environment, and has faster operation speed, and can work well for detection and tracking of similar depth objects.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.255-261
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• 2020

We consider the problem of autonomously flying a quadcopter in indoor environments. Navigation in indoor settings poses two major issues. First, real time recognition of the marker captured by the camera. Second, The combination of the distributed images is used to determine the position and orientation of the quadcopter in an indoor environment. We autonomously fly a miniature RC quadcopter in small known environments using an on-board camera as the only sensor. We use an algorithm that combines data-driven image classification with image-combine techniques on the images captured by the camera to achieve real 3D localization and navigation.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.51-58
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• 2012

Recently, 3D technology based on depth image is widely used in various fields including 3D space recognition, image acquisition, interaction, and games. Depth camera is used in order to produce depth image, various types of effort are made to improve quality of the depth image. In this paper, we suggests using area-based Canny edge detector to improve depth image in applying 3D technology based on depth camera. The suggested method provides improved depth image with pre-processing and post-processing by fixing image quality deterioration, which may take place in acquiring depth image in a limited environment. For objective image quality evaluation, we have confirmed that the image is improved by 0.42dB at maximum, by applying and comparing improved depth image to virtual view reference software. In addition, with DSCQS(Double Stimulus Continuous Quality Scale) evaluation method, we are reassured of the effectiveness of improved depth image through objective evaluation of subjective quality.

• Cartoon and Animation Studies
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• s.36
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• pp.45-74
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• 2014

We can anticipate that animations will form one of the axes and lead popular culture in our future visual age. Recently, research has been actively conducted, but it mainly focuses on their value in culture industry or technologies and methods of producing animations. Of course, research that deals with animation characters has constantly come out. This study focuses on the 'formative elements' of 3D animation characters and attempts differentiation from other research by inducing new logic theoretically. Being freed from the research on characters that has been merely focused on theoretical grounds, this study intends to figure out how audience that is consumers who actually get to watch and feel animations recognizes them and find out related problems and also solutions for them. In particular, this study intends to examine the formative characteristics of 3D animation characters with the characters appearing in , one of the animations that have achieved artistic value as well as commercial success. And for that, the study conducted not only literature review but various surveys and Delphi method as well. Also, the researcher devised an analysis frame to evaluate the formative elements through in-depth discussion with experts. And with this, the study created the forms such as the Elements of Form, Formation Methods of Form and Visual Recognition Elements of Form, examined how audience recognized 3D characters. The process of recognizing an image is influenced by socio-cultural environment or sex, age, and the level of knowledge differently. This was meant to investigate current visual culture and the public's perspective through characters in that represent the visual mode.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.3
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• pp.247-256
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• 2012

Stable carbon isotope ratio of oil components are known to be unaffected by weathering processes and thus has been widely used to determine the origin of spilled oil. In this study, molecular index and composition of stable carbon isotope in 15 crude oils and petroleum product were analyzed and used as oil fingerprints to determine the discriminating power of each fingerprinting method among target crude oils. Through the fingerprints of alkane distribution only Bintulu and B-C(1%) were distinguishable from other crude oils. The pristane/phytane ratio can classify the crude oils into three groups but differentiation of crude oils within a group was impossible using the ratio. The crude oils of A.L., A.S.L., Foroozan and B-C(1%) were differentiated from the other oils using PAH source recognition indexes of C2D/C2P and C3D/C3P. The usage of 4-mD/1-mD and 2/3-mD/1-mD ratio was able to distinguish A.S.L., Bintulu and Oman from the other crude oils. However the PAH source recognition ratios in the other crude oils were similar and thus they were impractical to be used for source identification among the target crude oils. Stable carbon isotope ratios of alkanes were able to uniquely specify each crude oil in the plot of ${\delta}^{13}C_{C21}$ and ${\delta}^{13}C_{C25}$ except A.L., A.M., Qatar-Marine, B-C(1%). The oil fingerprinting method using stable carbon isotope ratios of individual alkane compounds showed more discriminating power among the target crude oils than the conventional source recognition indexes of PAHs or alkanes.

• Journal of the Korean housing association
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• v.8 no.3
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• pp.141-151
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• 1997

This study was conducted to examine the environmental factors of apartments and therefore to suggest elements necessary to plan environments by evaluating and analysing both reside environments and conditions with residents at high-rise apartments in Kumi city. Kyongbuk. Korea. The result of this study is summarized as follows: 1) The motive of residence at apartment showed mainly the better environment of nature. and that the locational condition of those apartments was considered as a good standard for evaluating the apartment. 2) The evaluation of satisfaction showed that residents residing at apartment A tended to be satisfaied with all factors other than ‘complex’ although there was wholly dissatisfaction. In addition. it was shown that apartment B was satisfaied with housing and complex. apartment C with comfort. respectively. and apartment D with housing. 3) The evaluation of image showed that apartment C indicated the lowest variety of its complex while other factors were highly considered. Their image concerning residence was highest in apartment A. most lowest in apartment C. Then. apartment B showed the highest familiarity with and recognition of apartment complex.

• Knowledge Management Research
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• v.13 no.3
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• pp.17-36
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• 2012

With wide recognition of significant roles of venture companies in economic and industrial developments, substantial academic attention has been paid to understanding venture success and numerous policy measures have been made to help them. A serious problem, however, is that only a few limited number of venture could successfully grow to be large firm. The goal of this paper is to identify critical factors to drive 'leapfrogging' growth of venture companies by analyzing the success cases in Daejeon area. The theoretical analysis and case study suggest 1) founders' entrepreneurship continuity as a significant internal organization factor for growth and highlight importance of 2) exploring foreign markets and globalization of business operation in the early stage of growth. Furthermore, the research results identify two critical innovation strategies, 3) ambidextrous R&D strategy and 4) open innovation strategy, for entrepreneurial founders to effectively catch the business chances brought by environment change.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1477-1484
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• 2015

With the growth of financial industry with smartphone, interest on user authentication using smartphone has been arisen in these days. There are various type of biometric user authentication techniques, but gait recognition using accelerometer sensor in smartphone does not seem to develop remarkably. This paper suggests the method of user authentication using accelerometer sensor embedded in smartphone. Specifically, calibrate the sensor data from smartphone with 3D-transformation, extract features from transformed data and do principle component analysis, and learn model with using gaussian mixture model. Next, authenticate user data with confidence interval of GMM model. As result, proposed method is capable of user authentication with accelerometer sensor on smartphone as a high degree of accuracy(about 96%) even in the situation that environment control and limitation are minimum on the research.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.79-87
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• 2014

In this paper, we implemented the HearCAM platform with Raspberry PI B+ model which is an open source platform. Raspberry PI B+ model consists of dual step-down (buck) power supply with polarity protection circuit and hot-swap protection, Broadcom SoC BCM2835 running at 700MHz, 512MB RAM solered on top of the Broadcom chip, and PI camera serial connector. In this paper, we used the Google speech recognition engine for recognizing the voice characteristics, and implemented the pattern matching with OpenCV software, and extended the functionality of speech ability with SVOX TTS(Text-to-speech) as the matching result talking to the microphone of users. And therefore we implemented the functions of the HearCAM for identifying the voice and pattern characteristics of target image scanning with PI camera with gathering the temperature sensor data under IoT environment. we implemented the speech recognition, pattern matching, and temperature sensor data logging with Wi-Fi wireless communication. And then we directly designed and made the shape of HearCAM with 3D printing technology.