• Smart Structures and Systems
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• v.30 no.4
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• pp.385-395
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• 2022

Detecting cracks on a concrete structure is crucial for structural maintenance, a crack being an indicator of possible damage. Conventional crack detection methods which include visual inspection and non-destructive equipment, are typically limited to a small region and require time-consuming processes. Recently, to reduce the human intervention in the inspections, various researchers have sought computer vision-based crack analyses: One class is filter-based methods, which effectively transforms the image to detect crack edges. The other class is using deep-learning algorithms. For example, convolutional neural networks have shown high precision in identifying cracks in an image. However, when the objective is to classify not only the existence of crack but also the types of cracks, only a few studies have been reported, limiting their practical use. Thus, the presented study develops an image processing procedure that detects cracks and classifies crack types; whether the image contains a crazing-type, single crack, or multiple cracks. The properties and steps in the algorithm have been developed using field-obtained images. Subsequently, the algorithm is validated from additional 227 images obtained from an open database. For test datasets, the proposed algorithm showed accuracy of 92.8% in average. In summary, the developed algorithm can precisely classify crazing-type images, while some single crack images may misclassify into multiple cracks, yielding conservative results. As a result, the successful results of the presented study show potentials of using vision-based technologies for providing crack information with reduced human intervention.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.7
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• pp.3-14
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• 2006

The objective of this study was to develop a GIS-based decision support system (GIS-USLE system) to estimate soil erosion and evaluate its effect on concentrated upland plots in Godang district, Korea. This system was developed for the ArcView environment using A VENUE script. Three modules were used in the GIS-USLE system, namely pre-processing, the USLE factors calculator module, and post-processing. This system benefits from a user friendly environment that allows users with limited computer knowledge to use it. This system was applied to 1,285 individual upland plots ranging from 0.005 to 1.347 ha in size with an average slope steepness of 14 %. The rainfall distributions were estimated using the three methods, namely Mononobe and Yen-Chow with Triangle and with Trapezoid type, and then used to calculate the rainfall erosivity factor. The soil erosion amounts from the 1,285 individual plots in the study area by 2 year return period with a 24h maximum rainfall amount of 154.6 mm were estimated at 5 tons/ha on average. Slope appeared to be the most important factor affecting soil erosion estimation, as expected. The prototype model was applied to the project area, and the results appeared to support the practical applications. By examining many fields simultaneously, this system can easily provide fast estimation of soil erosion and thus reveal the spatial pattern of erosion from fields in a region. This study will help estimate and evaluate soil erosion in concentrated upland districts and identify the best management practices.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.4
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• pp.195-204
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• 2010

Due to improved wireless communication technologies, it is possible to provide multimedia streaming service for mobile device clients like PDAs and cellphones. Wireless networks are serviced on low bandwidth channels and mobile devices work on limited hardware specifications. In these conditions, transcoding technologies are needed to adapt the media for streaming services to given mobile environments. To transcode from the source media to the target media for corresponding grades, transcoding servers perform transcoding jobs as exhausting their resources. Since various transcoding loads occur according to the target transconding grades, an effective transcoding load balancing policy is required among transcoding servers. In addition to transcoding process, servers should maintain QoS streams for mobile clients for total serviced times. It requires real-time requirements to support QoS for various mobile clients. In this paper, a new transcoding load distribution method is proposed. The proposed method can be driven for fair load balance between distributed transcoding servers. Based on estimated transcoding time, movie information and target transcoding bit-rate, it provides fair transcoding load distribution and also performs admission control to support QoS streams for mobile clients.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.401-406
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• 2015

In this study, the gait imbalance evaluation algorithm based on two axes angle using encoder is proposed. This experiment was carried out to experiment with a healthy adult male to 10 people. The device is attached to the hip and knee joint in order to measure the angle during the gait. Normal and imbalance gait angle data were measured using an encoder attached to the hip and knee joints. Also, in order to verify the reliability of estimation of asymmetrical gait using hip and knee angle, it was compared with the result of asymmetrical gait estimation using foot pressure. SI (Symmetry Index) was used as an index for determining the gait imbalance. As a result, normal gait and 1.5cm imbalance gait were evaluation as normal gait through SI using an encoder. And imbalance gait of 3cm, 4cm, and 6cm were judge by imbalance gait. Whereas all gait experiments except normal gait were evaluation as imbalance gait through SI using the pressure. It was possible to determine both the normal gait and imbalance gait through measurement for the angle and the pressure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1872-1879
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• 2001

As multiview video applications become more popular, correspondence problem for stereo image matching plays an important role in expanding view points. Thus, we propose an efficient dense disparity estimation algorithm considering features of each image pair of multiview image sets. Main concepts of the proposed algorithm are based on the region-dividing-bidirectional-pixel-matching method. This algorithm makes matching process efficient and keeps the reliability of the estimated disparities. Other improvement have obtained by proposed cost function, matching window expanding technique, disparity regularization, and disparity assignment in ambiguous region. These techniques make disparities more stable by removing false disparities and ambiguous regions. The estimated disparities are used to synthesize intermediate views of multiview images. Computer simulation demonstrates the excellence of the proposed algorithm in both subjective and objective evaluations. In addition, processing time is reduced as well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.156-163
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• 2013

The use of an error-correcting code is essential in communication systems where the channel is noisy. When channel coding parameters are unknown at a receiver side, decoding becomes difficult. To perform decoding without the channel coding information, we should estimate the parameters. In this paper, we introduce a method to reconstruct the generator polynomial of BCH(Bose-Chaudhuri-Hocquenghem) codes based on the idea that the generator polynomial is compose of minimal polynomials and BCH code is cyclic code. We present a probability compensation method to improve the reconstruction performance. This is based on the concept that a random data pattern can also be divisible by a minimal polynomial of the generator polynomial. And we confirm the performance improvement through an intensive computer simulation.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.713-720
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• 2018

The Signal Intelligence (SIGINT) system based on Angle-of-Arrival(AOA) estimation, interference suppression, and transmission beamforming techniques is a cutting edge technology for efficiently collecting various signal information. In this paper, we present the efficient structure of a satellite system consisted of an AOA estimator, an adaptive beamformer, a signal processing and D/B unit, and a transmission beamformer, for collecting signal information. For accurately estimating AOAs of various signals, efficiently suppressing interference or jamming signals, and efficiently transmitting the collected information or data, we employ Multiple Signal Classification (MUSIC), Minimum Variance Distortionless Response (MVDR), and Minimum Mean Square Error (MMSE) algorithms, respectively. Also, we evaluate and analysis the performance of the presented satellite system through the computer simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.383-393
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• 2010

DVC (Distributed Video Coding) allows us to explore the video statistics at the decoder side, resulting in a less complex encoder and more complex decoder. In this approach, it is important to generate a good prediction to the current Wyner-Ziv frame, called side information, which plays a crucial role in the overall performance of a DVC system. Conventional MCFI (motion compensated frame interpolation) techniques, which explore temporal correlations between neighbor frames of the current frame, preform the block-based or object-based motion estimation, but, they do not include the basis frame for the Wyner-Ziv frame. This paper proposes an efficient way to get better side information, by finding the average frame between neighbor frames and by comparing adaptively the candidate blocks. Through computer simulations, it is shown that the proposed method can improve the performance up to 0.4dB and provide better subjective and objective visual qualities in Wyner-Ziv CODEC.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.15-21
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• 2018

In this study, we try to detect anomalies on the network intrusion detection system by learning only one class. We use KDD CUP 1999 dataset, an intrusion detection dataset, which is used to evaluate classification performance. One class classification is one of unsupervised learning methods that classifies attack class by learning only normal class. When using unsupervised learning, it difficult to achieve relatively high classification efficiency because it does not use negative instances for learning. However, unsupervised learning has the advantage for classifying unlabeled data. In this study, we use one class classifiers based on support vector machines and density estimation to detect new unknown attacks. The test using the classifier based on density estimation has shown relatively better performance and has a detection rate of about 96% while maintaining a low FPR for the new attacks.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.377-385
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• 2015

This paper proposes a novel forward vehicle tracking algorithm based on the WMIL(Weighted Multiple Instance Learning) equipped with a particle filter. In the proposed algorithm Haar-like features are used to train a vehicle object detector to be tracked and the location of the object are obtained from the recognition result. In order to combine both the WMIL to construct the vehicle detector and the particle filter, the proposed algorithm updates the object location by executing the propagation, observation, estimation, and selection processes involved in particle filter instead of finding the credence map in the search area for every frame. The proposed algorithm inevitably increases the computation time because of the particle filter, but the tracking accuracy was highly improved compared to Ababoost, MIL(Multiple Instance Learning) and MIL-based ones so that the position error was 4.5 pixels in average for the videos of national high-way, express high-way, tunnel and urban paved road scene.