• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.23-31
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• 2000

Iterative curve evolution techniques are powerful methods for image segmentation. Classical methods proposed curve evolutions which guarantee close contours at convergence and, combined with the level set method, they easily handled curve topology changes. In this paper, we present a new geometric active contour model based on level set methods introduced by Osher & Sethian for detection of object boundaries or shape and we adopt anisotropic diffusion filtering method for removing noise from original image. Classical methods allow only one-way curve evolutions : shrinking or expanding of the curve. Thus, the initial curve must encircle all the objects to be segmented or several curves must be used, each one totally inside one object. But our method allows a two-way curve evolution : parts of the curve evolve in the outward direction while others evolve in the inward direction. It offers much more freedom in the initial curve position than with a classical geodesic search method. Our algorithm performs accurate and precise segmentations from noisy images with complex objects(jncluding sharp angles, deep concavities or holes), Besides it easily handled curve topology changes. In order to minimize the processing time, we use the narrow band method which allows us to perform calculations in the neighborhood of the contour and not in the whole image.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.13-21
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• 2011

In mobile environment supporting mobility technologies, user requirements have been increased with respect to utilization of location information. In particular, moving object DBMS has consistently posed in order to efficiently maintain traffic information related to location of vehicle which tents to tremendously change over time. Despite the fact that these sorts of researches must be taken into consideration, empirical studies on moving object in terms of map database for lbs service, spatial attribute of which is continuously changed over time, have rarely performed. Therefore, aim of this paper is to suggest efficient spatial index scheme, which is capable of supporting query processing algorithm and location of moving object over time, by developing new empirical model. As a result, we can come to the conclusion that moving object model based on multi-fixed grid index makes it possible to cut down on the number of entity for retrieving. What's more, this model enables hierarchical data to be accessed through efficient spatial filtering on large-scale lbs data and constraints in accordance with level in order to display map.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.291-297
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• 2004

In this paper, a new structure for the AEC(Acoustic Echo Canceller) is proposed in which echo signal components that can be created in mobile communications is effectively eliminated. Block Data Flow Architecture is a parallel architecture that achieves high performance, high efficiency, high throughput, and almost linear speed up. The proposed architecture employs AEC and is implemented using the TMS320C6711 for real-time applications. The proposed AEC shows improved performance by eliminating echoes at 55ms delay path. Since the proposed AEC can also be implemented in Firmware, it is believed to effectively work on various types of echoes if it is applied on CDMA mobile devices. The TMS320C6711 shows much better performance comparing to previous DSPs. For experimental verifications, filtering operation using adaptive algorithm is performed on TMS320C6711 board and error signals resulted from computations are monitored on PC, and then the performance of the implemented AEC is verified through ERLE computation. According the results of simulation, good characteristic of 100dB are shown after 500 sampling data.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.31-46
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• 2009

An Unscented Kalman Filter (UKF) for estimation of the attitude and rate of a spacecraft using only magnetometer vector measurement is developed. The attitude dynamics used in the estimation is the nonlinear Euler's rotational equation which is augmented with the quaternion kinematics to construct a process model. The filter is designed for small satellite in low Earth orbit, so the disturbance torques include gravity-gradient torque, magnetic disturbance torque, and aerodynamic drag torque. The magnetometer measurements are simulated based on time-varying position of the spacecraft. The filter has been tested not only in the standby mode but also in the detumbling mode. Two types of actuators have been modeled and applied in the simulation. The PD controller is used for the two types of actuators (reaction wheels and thrusters) to detumble the spacecraft. The estimation error converged to within 5 deg for attitude and 0.1 deg/s for rate respectively when the two types of actuators were used. A joint state parameter estimation has been tested and the effect of the process noise covariance on the parameter estimation has been indicated. Also, Monte-Carlo simulations have been performed to test the capability of the filter to converge with the initial conditions sampled from a uniform distribution. Finally, the UKF performance has been compared to that of the EKF and it demonstrates that UKF slightly outperforms EKF. The developed algorithm can be applied to any type of small satellites that are actuated by magnetic torquers, reaction wheels or thrusters with a capability of magnetometer vector measurements for attitude and rate estimation.

• Journal of Convergence Society for SMB
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• v.1 no.1
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• pp.39-44
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• 2011

Recently, due to people's incontinent use all over the world, fossil fuels such as coal, oil, and natural gas were nearly to be exhausted and also causes serious environment pollutions. Therefore, there is a strong need to develop solar, wind, hydro, biomass, geothermal to replace fossil fuels to prevent suffering from above problems. Wish advances in sensor technology, such data is collected as a kind of stream data which arrives in an online manner so that it is characterized as high- speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. Therefore, the traditional data processing techniques are not fit to deal with stream data. In this paper, we propose a kalman filter-based algorithm to process renewable stream data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.55-62
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• 2016

Recently, users choosing a restaurant basedon information provided by blogs are increasing significantly. However, those of most blogs are unreliable since domestic restaurant blogs are occupied by advertising postings written by 'power bloggers'. Thus, in order to ensure the reliability of blogs, it is necessary to filter the advertising blogs which are sometimes false or exaggerated. In this paper, we propose the method of distinguishing the advertising blogs utilizing an automatic classification technique. In the proposed technique, we first manually collected advertising restaurant blogs, and then analyzed features which are commonly found in those blogs. Using the extracted features, we determined whether a given blog is advertising one applying automatic classification algorithms. Additionally, we select the features and the algorithm which guarantee optimal classification performance through comparative experiments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.1
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• pp.74-82
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• 2008

The objective of this paper is to remove noises of image based on the heuristic noises filter and to extract a tumor region by using morphology techniques in breast ultrasound image. Similar objective studies have been conducted based on ultrasound image of high resolution. As a result, efficiency of noise removal is not fine enough for low resolution image. Moreover, when ultrasound image has multiple tumors, the extraction of ROI (Region Of Interest) is not accomplished or processed by a manual selection. In this paper, our method is done 4 kinds of process for noises removal and the extraction of ROI for solving problems of restrictive automated segmentation. First process is that pixel value is acquired as matrix type. Second process is a image preprocessing phase that is aimed to maximize a contrast of image and prevent a leak of personal information. In next process, the heuristic noise filter that is based on opinion of medical specialist is applied to remove noises. The last process is to extract a tumor region by using morphology techniques. As a result, the noise is effectively eliminated in all images and a extraction of tumor regions is possible though one ultrasound image has several tumors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.19-26
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• 2006

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor (EHD) is time consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by the only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.167-172
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• 2002

Recently, some of people are keep in research and development of the further more efficient and convenient auction systems using intelligent software agents in electronic commerce. The purpose of this thesis is that a simple auction system has web bulletin boards, is aided by intelligent agent, and generates pertinent auction duration time and starting price for auction goods of auctioneer into a auction system, then the auctioneer gets the highest margin. The seller who want to sell goods, is using internet sends mail that has information for goods to agent of internet auction system. The agent undertake filtering process for already learned information about similar goods. And it calculate duration time and start price from stored bidding history database. In this thesis we propose a mailing agent system pushing information in internet auction that enables to aid decision for auctioneer about the starting time and price which delivers the highest margin.

• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.107-116
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• 2013

In this paper, we propose a hybrid music recommendation system combining users' listening habits and tag information in a social music site. Most of commercial music recommendation systems recommend music items based on the number of plays and explicit ratings of a song. However, the approach has some difficulties in recommending new items with only a few ratings or recommending items to new users with little information. To resolve the problem, we use tag information which is generated by collaborative tagging. According to the meaning of tags, a weighted value is assigned as the score of a tag of an music item. By combining the score of tags and the number of plays, user profiles are created and collaborative filtering algorithm is executed. For performance evaluation, precision, recall, and F-measure are calculated using the listening habit-based recommendation, the tag score-based recommendation, and the hybrid recommendation, respectively. Our experiments show that the hybrid recommendation system outperforms the other two approaches.