• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.4
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• pp.193-205
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• 2003

There has been so many research activities about robot soccer system in the many research fields, for example, intelligent control, communication, computer technology, sensor technology, image processing, mechatronics. Especially researchers research strategy for attacking in the field of strategy, and develop intelligent strategy. Then, soccer robots cannot defense completely and efficiently by using simple defense strategy. Therefore, intention extraction of attacker is needed for efficient defense. In this thesis, intention extractor of soccer robots is designed and developed based on FMMNN(Fuzzy Min-Max Neural networks ). First, intention for soccer robot system is defined, and intention extraction for soccer robot system is explained.. Next, FMMNN based intention extractor for soccer robot system is determined. FMMNN is one of the pattern classification method and have several advantages: on-line adaptation, short training time, soft decision. Therefore, FMMNN is suitable for soccer robot system having dynamic environment. Observer extracts attack intention of opponents by using this intention exactor, and this intention extractor is also used for analyzing strategy of opponent team. The capability of developed intention extractor is verified by simulation of 3 vs. 3 robot succor simulator. It was confirmed that the rates of intention extraction each experiment increase.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.524-527
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• 2008

Recently, digital and the Internet are widespread out of the world, and multimedia processing technology and the development of information and communication technology in education using the Internet as the demand is rapidly increasing. Also, we tan easily use informations with less restrictions of time and space. however, several kinds of audio, media to integrate multimedia data, such as the proliferation of demands for representation. Therefore, in 1998, W3C presented an international standard, SMIL in order to solve multimedia object representation and synchronization problems. By using SMIL, various multimedia elements can be integrated as a multimedia document with proper view in a spate and time. Using this SMIL document, we can create new internet radio broadcasting service that delivers not noly audio data but also various text, image and video. In this paper, with the system, teachers can easily create multimedia courseware and living broadcast their torture on network, students can receive audio-video information of the teacher, screen displays of the teachers computer. Moreover students can communicate with teacher simultaneously by text editor windows. Students can also order courseware after class.

• Journal of the Korean Wood Science and Technology
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• v.38 no.6
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• pp.532-540
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• 2010

The strength properties of wooden model retaining wall made of pitch pine (Pinus rigida Miller) was evaluated. Three different types of wooden model retaining wall were made of the 11cm square timber treated with CUAZ-2 (Copper Azole). The retaining wall was made into the 4 layers of crossbar and the 3 layers of vertical-bar, of which the size was 86 cm high, 200 cm long and 96 cm wide. Type I was control and in Type II 20 cm vertical-bars and 93 cm vertical-bars were arranged alternately to decrease wood usage. TypeIII was similar to TypeII except that the connection between crossbars was reinforced with the wooden armature. In each type, the strength properties of retaining wall were investigated by horizontal loading test and the deformation of structure by image processing (AICON 3D DPA-PRO system). In horizontal loading test of Type I, Type II and Type III was 63.17, 57.80, and 60.97 kN/m, respectively. The deformation of the top layer in Type II was 1.5 times larger than in Type I and Type III. Consequently, the economic efficiency and strength performance were better in Type III than in Type I and Type II.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.165-172
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• 2017

High frequency squeal noise can be generated when a railroad vehicle runs a sharp curved section; this noise causes environmental complaints and excessive wear on the wheel and the railroad track. In this paper, curved squeal noise experiments on a commercial railway were carried out to investigate this phenomenon. The relationship of the squeal noise pressure level, the frequency characteristics, the railway running speed, and the modal behavior of the wheel were investigated. At the same time, the lateral motion of the wheel relative to the rail was captured using a video camera; wheel movement was calculated when the noise was generated. queal noise occurred at the highest level at the inner front wheel; this phenomena is considered to be related to the lateral vibration response characteristics of the wheel. It can be seen that the magnitude of this squeal noise is not directly related to the increase in vehicle speed.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.3
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• pp.261-270
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• 2017

Bad sitting postures are known to cause for a variety of diseases or physical deformation. However, it is not easy to fit right sitting posture for long periods of time. Therefore, methods of distinguishing and inducing good sitting posture have been constantly proposed. Proposed methods were image processing, using pressure sensor attached to the chair, and using the IMU (Internal Measurement Unit). The method of using IMU has advantages of simple hardware configuration and free of various constraints in measurement. In this paper, we researched on distinguishing sitting postures with a small amount of data using just one IMU. Feature extraction method was used to find data which contribution is the least for classification. Machine learning algorithms were used to find the best position to classify and we found best machine learning algorithm. Used feature extraction method was PCA(Principal Component Analysis). Used Machine learning models were five : SVM(Support Vector Machine), KNN(K Nearest Neighbor), K-means (K-means Algorithm) GMM (Gaussian Mixture Model), and HMM (Hidden Marcov Model). As a result of research, back neck is suitable position for classification because classification rate of it was highest in every model. It was confirmed that Yaw data which is one of the IMU data has the smallest contribution to classification rate using PCA and there was no changes in classification rate after removal it. SVM, KNN are suitable for classification because their classification rate are higher than the others.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.499-501
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• 2016

In this paper, we suggest an advance method for maintaining a perceived behavior as triangle formation and preventing collision between each other in case of a flying drone. In the existing studies, the collision of the drone is only controlled by using light entered in the camera or the image processing. However, when there is no light, it is difficult to confirm the position of each other and they can collide because this system can not confirm the each other's position. Therefore, in this paper, we propose the system to solve the problems by using the distance and the relative coordinates of the three drones that were determined using the ALPS(Ad hoc network Localized Positioning System) algorithm. This system can be a new algorithm that will prevent collisions between each other during flying the drone object. The proposed algorithm is that we make drones maintaining a determined constant value of the distance between coordinates of each drone and the measured center of the drone of triangle formation. Therefore, if the form of fixed formation is disturbed, they reset the position of the drone so as to keep the distance between each drone and the center coordinates constant. As a result of the simulation, if we use the system where the supposed algorithm is applied, we can expect that it is possible to prevent malfunction or an accident due to collisions by preventing collisions of drones in advanced behavior system.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.173-184
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• 2008

Development of an accident estimation model based on accident data can be made after accident occurrences. However, the taking of historical accident data is not easy, and there have been differences between real accident data and police-reported accident data. Also, another difficult shortcoming is that historical traffic accident data better consider driver behavior or intersection characteristics. A new method needs to be developed that can predict accident occurrences for traffic safety improvement in black spots. Traffic conflict decision techniques can acquire and analyze data in time and space, requiring less data collection through investigation. However, there are shortcomings: as existing traffic conflict techniques do not operate automatically, the analyst's opinion could easily affect the study results. Also, existing methods do not consider the severity of traffic conflicts. In this study, the authors presented traffic conflict decision criteria which consider conflict severity, including opposing left turn traffic conflict and cross traffic conflict decision criteria. In order to test these criteria, the authors acquired three signalized intersection images (two intersections in Sungnam city and one intersection in Paju) and analyzed the acquired images using image processing techniques based on individual vehicle tracking technology. Within the analyzed images, level 1 conflicts occurred 343 times over three intersections. Some of these traffic conflicts resulted in level 3 conflict situations. Level 3 traffic conflicts occurred 25 times. From the study results, the authors found that traffic conflict decision techniques can be an alternative to evaluate traffic safety in black spots.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1415-1425
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• 2018

Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.

• Journal of Conservation Science
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• v.37 no.3
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• pp.232-244
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• 2021

This study examined the physical attributes and heat treatment characteristics of glass beads excavated from the Gimhae area, which is the location of Geumgwan Gaya. This enabled classification of surface characteristics of the beads based on the investigation of the color, size, and shape. The glass beads were classified into eight color systems, with purplish-blue beads as the representative color. Bead size was categorized into three types depending on the outer diameter and how it increased over time. Bead shapes were categorized as round, tubular, or doughnut-shaped based on the inner diameter and length, with round being the typical shape. According to the degree of heat treatment, there are three types of cross-section for glass beads that are manufactured by the drawing technique, most of which are the HT-III type. In addition, it is estimated that the heat treatment technology has more considerable effects than other methods. Through non-destructive analysis, the chemical composition was obtained and categorized as flux, stabilizer, and colorant. Analysis confirmed the presence of 63 and 9 pieces in the potash and soda glass groups, respectively. Overall findings from the study highlighted a correlation between the chemical composition and the external factors such as color, size, shape, and manufacturing technology of glass beads recovered from Geumgwan Gaya, revealing characteristics related to that time and region.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1259-1268
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• 2021

The 2nd Geostationary Ocean Color Imager (GOCI-II) is the successor to the Geostationary Ocean Color Imager (GOCI), which employs one near-ultraviolet wavelength (380 nm) and eight visible wavelengths(412, 443, 490, 510, 555, 620, 660, 680 nm) and three near-infrared wavelengths(709, 745, 865 nm) to observe the marine environment in Northeast Asia, including the Korean Peninsula. However, the multispectral radiance image observed at satellite altitude includes both the water-leaving radiance and the atmospheric path radiance. Therefore, the atmospheric correction process to estimate the water-leaving radiance without the path radiance is essential for analyzing the ocean environment. This manuscript describes the GOCI-II standard atmospheric correction algorithm and its initial phase validation. The GOCI-II atmospheric correction method is theoretically based on the previous GOCI atmospheric correction, then partially improved for turbid water with the GOCI-II's two additional bands, i.e., 620 and 709 nm. The match-up showed an acceptable result, with the mean absolute percentage errors are fall within 5% in blue bands. It is supposed that part of the deviation over case-II waters arose from a lack of near-infrared vicarious calibration. We expect the GOCI-II atmospheric correction algorithm to be improved and updated regularly to the GOCI-II data processing system through continuous calibration and validation activities.