• Journal of information and communication convergence engineering
• /
• v.7 no.4
• /
• pp.535-538
• /
• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise to preserve edges. As the result, MAM of the proposed method enhances the image to about 10% in comparison with Winner filter by Edge Preservation Index and PSNR, and 10% to only adaptive median filtering.

• Proceedings of the KIEE Conference
• /
• 1989.11a
• /
• pp.393-396
• /
• 1989

This paper deals with the design of the adaptive controller using a decentralized control for Large-Scale system formed of an arbitrary interconnection of subsystem with unknown parameters, non linearity and bounded disturbance. In order to reduce the load and frequency deviations, now decentralized adaptive controllers are developed for stabilization and tracking the parameters. In the simulation studies of the decentralized adaptive control of a two-area interconnected power system, the effectiveness of the proposed adaptive is demonstrated.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.8 s.179
• /
• pp.2091-2099
• /
• 2000

The object of the present study is to present an adaptive wavelet-Galerkin method for the analysis of thin-walled box beam. Due to good localization properties of wavelets, wavelet methods emerge as alternative efficient solution methods to finite element methods. Most structural applications of wavelets thus far are limited in fixed-scale, non-adaptive frameworks, but this is not an appropriate use of wavelets. On the other hand, the present work appears the first attempt of an adaptive wavelet-based Galerkin method in structural problems. To handle boundary conditions, a fictitous domain method with penalty terms is employed. The limitation of the fictitious domain method is also addressed.

• Proceedings of the KIEE Conference
• /
• 2003.07a
• /
• pp.110-112
• /
• 2003

This paper presents an alleviant technique for solving ill-conditioned linear systems using spectral adaptive mapping, which is based on spectral mapping theorem. The conventional approaches to solve the ill-conditioned linear systems are divided into reformulation and alleviant technique. So far, the alleviant technique is evaluated the most effective one. In this paper, an adaptive mapping of spectrum is adopted to alleviate the condition number of ill-conditioned linear systems. A shift constant, which is a dominant factor of the spectral adaptive mapping that are proposed, is assessed by the system spectrum. The proposed spectral adaptive mapping technique is tested to demonstrated the validation on several size Hilbert matrices and small scale power systems, which are provide the promising results.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.6 no.1
• /
• pp.7-17
• /
• 1997

During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1993.06a
• /
• pp.45-49
• /
• 1993

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.10
• /
• pp.4929-4947
• /
• 2017

In visual object tracking, Correlation Filter-based Tracking (CFT) systems have arouse recently to be the most accurate and efficient methods. The CFT's circularly shifts the larger search window to find most likely position of the target. The need of larger search window to cover both background and object make an algorithm sensitive to the background and the target occlusions. Further, the use of fixed-sized windows for training makes them incapable to handle scale variations during tracking. To address these problems, we propose two layer target representation in which both global and local appearances of the target is considered. Multiple local patches in the local layer provide robustness to the background changes and the target occlusion. The target representation is enhanced by employing additional reversed RGB channels to prevent the loss of black objects in background during tracking. The final target position is obtained by the adaptive weighted average of confidence maps from global and local layers. Furthermore, the target scale variation in tracking is handled by the statistical model, which is governed by adaptive constraints to ensure reliability and accuracy in scale estimation. The proposed structural enhancement is tested on VTBv1.0 benchmark for its accuracy and robustness.

• Proceedings of the Korean Information Science Society Conference
• /
• 2008.06d
• /
• pp.322-326
• /
• 2008

시스템의 규모가 대형화되어 감에 '시스템의 시스템'의 형태로써 대규모 사이즈의 프로그램 다양한 목적을 가진 사용자들, 대규모 저장 데이터양과 처리, 소프트웨어 컴포넌트간의 복잡한 연결상과 상호 의존성, 하드웨어의 다양성등을 포함하는 초대형 규모로 발전하고 있다. 또한 유, 무선 인터넷의 보편화와 소형기기들의 인터넷화 및 기존 서비스들의 개방화가 진행됨에 따라 새로운 독자적인 서비스를 만들기 보다는 SOA기반의 기존 시스템을 통합하여 새로운 서비스를 만드는 시도가 일어나고 있다. 최근 진행되고 있는 국가 및 산업의 대형 프로젝트들은 이러한 흐름에 따라 IT기술을 융합한 소프트웨어 기반의 초 대형 시스템 (Ultra Large Scale System)을 필요로 하고 있다. 이에 본 논문에서는 이러한 정보와 시스템의 대규모화에 대한 즉각적인 대처를 할 수 있는 Ultra Large Scale 시스템의 자율적응형 (Self-Adaptive) 기술 연구를 위하여 Self-Healing, Self-Integrating, Self-Orchestrating, Self-Managing, Self-Adaptring의 5가지 관점에서의 연구를 제안한다. 본 논문에서 제안하고 있는 연구의 파급 효과를 극대화 할 수 있는 영역은 e-Biz 시스템 u-city 시스템, USN 기반 물류 시스템 자동차 및 조선 사업의 IT융합 등의 대규모 시스템이 될 것이다.

• Journal of Korea Multimedia Society
• /
• v.14 no.4
• /
• pp.529-537
• /
• 2011

In this paper, we propose a stable scale adaptive tracking method that uses centroids of the target colors. Most scale adaptive tracking methods have utilized histograms to determine target window sizes. However, in certain cases, histograms fail to provide good estimates of target sizes, for example, in the case of occlusion or the appearance of colors in the background that are similar to the target colors. This is due to the fact that histograms are related to the numbers of pixels that correspond to the target colors. Therefore, we propose the use of centroids that correspond to the target colors in the scale adaptation algorithm, since centroids are less sensitive to changes in the number of pixels that correspond to the target colors. Due to the spatial information inherent in centroids, a direct relationship can be established between centroids and the scale of target regions. Generally, after the zooming factors that correspond to all the target colors are calculated, the unreliable zooming factors are filtered out to produce a reliable zooming factor that determines the new scale of the target. Combined with the centroid based tracking algorithm, the proposed scale adaptation method results in a stable scale adaptive tracking algorithm. It tracks objects in a stable way, even when the background colors are similar to the colors of the object.

• Journal of Digital Convergence
• /
• v.15 no.12
• /
• pp.661-667
• /
• 2017

The purpose of this study is to examine the effects of therapeutic horse riding on adult with intellectual disability in terms of adaptive behavior. The subjects were 16 adults with intellectual disability. They participated in a therapeutic horse riding program of 60 minutes long, Twice a week for 12 weeks. The participants' adaptive behavior level were measured before and after 12 weeks of program with Social Maturity Scale. The data was analyzed by paired t-test using the SPSS. After 12 weeks of therapeutic horse riding program, there was a significant improvements on self-help, task, self-regulation & socialization. However, locomotion, communication changes did not reach statistical significance. The result indicates that therapeutic horse riding has a positive effect on adults with intellectual disability in self-help, task, self-regulation & socialization. This study suggests that therapeutic horse riding could be considered an effective method on adults with intellectual disability to improve adaptive behavior.