• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.395-413
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• 2016

Image authentication is a technique aiming at protecting the integrity of digital images. Reversible image authentication has attracted much attention of researcher because it allows to authenticate tampered regions in the image and to reconstruct the stego image to its original version losslessly. In this paper, we propose a new, reversible image authentication scheme based on adaptive prediction error expansion (PEE) technique. In the proposed scheme, each image block is classified into smooth or complex regions. Then, according to the characteristic of each block, the authentication code is embedded adaptively to achieve high performance of tamper detection. The experimental results demonstrated that the proposed scheme achieves good quality of stego images. In addition, the proposed scheme has ability to reconstruct the stego image to its original version, if no modification is performed on it. Also demonstrated in the experimental results, the proposed scheme provides higher accuracy of tamper detection than state-of-the-art schemes.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.3
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• pp.73-82
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• 1992

An industrial robot, installed real manufacturing processes an element of the system autmation, can be considered as an uncertain system due to dynamic uncertainties in inertial parameters and varying payloads. Most difficuties in controlling a robot manipulator are caused by the fact that the dynamic equations describing the motions of the manipulator are inherently nonlinear and heavily coupled effects between joints and associated links. Existing robot conrol systems have constant predefined gains and do not cover the complex dynamic interactions between manipulator joints. As a result, the manipulator is severly limited in range of application, speed of operation and variation of payload. The proposed controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories defined by the desinger. The proposed manipulator studied has two loops, an inner loop of model reference adaptive controller and an outer loop of state feedback controller with integral action to guarantee the stability of the adaptive scheme. This adaptation algorithm is based on the hyperstailiy approach with an improved Lyapunov function. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance in practical working environment, various load variations and parameter uncertainties.

• Smart Structures and Systems
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• v.4 no.6
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• pp.795-807
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• 2008

A challenging problem in structural damage detection based on vibration data is the requirement of a large number of sensors and the numerical difficulty in obtaining reasonably accurate results when the system is large. To address this issue, the substructure identification approach may be used. Due to practical limitations, the response data are not available at all degrees of freedom of the structure and the external excitations may not be measured (or available). In this paper, an adaptive damage tracking technique, referred to as the sequential nonlinear least-square estimation with unknown inputs and unknown outputs (SNLSE-UI-UO) and the sub-structure approach are used to identify damages at critical locations (hot spots) of the complex structure. In our approach, only a limited number of response data are needed and the external excitations may not be measured, thus significantly reducing the number of sensors required and the corresponding computational efforts. The accuracy of the proposed approach is illustrated using a long-span truss with finite-element formulation and an 8-story nonlinear base-isolated building. Simulation results demonstrate that the proposed approach is capable of tracking the local structural damages without the global information of the entire structure, and it is suitable for local structural health monitoring.

• Journal of Power Electronics
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• v.15 no.4
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• pp.1093-1104
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• 2015

A standard repetitive controller (RC) is theoretically able to replace a bank of resonant controllers in harmonic signals tracking applications. However, the traditional RC has some drawbacks such as a poor dynamic response and a complex structure to compensate grid frequency deviations for an effective unified power quality conditioner (UPQC) control scheme. In order to solve these problems, an improved RC with an outstanding dynamic response and a simplified grid frequency adaptive scheme is proposed for UPQC control systems in this paper. The control strategy developed for the UPQC has delay time, i.e., one-sixth of a fundamental period (T_p/6), repetitive controllers. As a result, the UPQC system can provide a fast dynamic response along with good compensation performance under both nonlinear and unbalanced loads. Furthermore, to guarantee the excellent performance of the UPQC under grid frequency deviations, a grid frequency adaptive scheme was developed for the RC using a simple first order Padé's approximation. When compared with other approaches, the proposed control method is simpler in structure and requires little computing time. Moreover, the entire control strategy can be easily implemented with a low-cost DSP. The effectiveness of the proposed control method is verified through various experimental tests.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.6
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• pp.623-632
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• 2013

Electromagnetic topology simplifies a complex analysis area in accordance with electromagnetic coupling. And then electromagnetic topology divides the simplified continuous area into sub-areas and analyzes electromagnetic problems at the sub-areas. Therefore electromagnetic topology has a merit to analyze the electromagnetic coupling in large and complex systems, however simplified modeling technique can generate large errors. In this paper, power balance method is used to estimate errors and subdivide junctions in the electromagnetic topology. The method is applied to analyze conducted and radiated electromagnetic coupling in two kinds of cavity models. Improvement of accuracy was accomplished in accordance with junction subdivision. Moreover we could save computation time and memory comparing with FDTD results.

• World Technopolis Review
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• v.5 no.1
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• pp.47-60
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• 2016

In today's digital non-linear global business environment, innovation initiatives are influenced by inter-organizational, political, economic, environmental, technological systems, as well as by decisions made individually by key actors in these systems. Network-based structures emerge from social linkages and collaborations among various actors, creating innovation ecosystems, complex adaptive systems in which entities co-create value. A shared vision of value co-creation allows people operating individually to arrive together at the same future. Yet, relationships are difficult to see, continually changing and challenging to manage. The Innovation Ecosystem Transformation Framework construct includes three core components to make innovation relationships visible and articulate networks of relational capital for the wellbeing, sustainability and business success of innovation ecosystems: data-driven visualizations, storytelling and shared vision. Access to data facilitates building evidence-based visualizations using relational data. This has dramatically altered the way leaders can use data-driven analysis to develop insights and provide ongoing feedback needed to orchestrate relational capital and build shared vision for high quality decisions about innovation. Enabled by a shared vision, relational capital can guide decisions that catalyze, support and sustain an ecosystemic milieu conducive to innovation for business growth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5394-5409
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• 2019

The paper investigates a novel detector receiver with Kalman channel information estimator and iterative channel response equalization for MIMO (multi-input multi-output) OFDM (orthogonal frequency division multiplexing) communication systems in fast multipath fading environments. The performances of the existing linear equalizers (LE) are not good enough over most fast fading multipath channels. The existing adaptive equalizer with decision feedback structure (ADFE) can improve the performance of LE. But error-propagation effect seriously degrades the system performance of the ADFE, especially when operated in fast multipath fading environments. By considering the Kalman channel impulse response estimation for the fast fading multipath channels based on CE-BEM (complex exponential basis expansion) model, the paper proposes the iterative receiver with soft decision feedback equalization (SDFE) structure in the fast multipath fading environments. The proposed SDFE detector receiver combats the error-propagation effect for fast multipath fading channels and outperform the existing LE and ADFE. We demonstrate several simulations to confirm the ability of the proposed iterative receiver over the existing receivers.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.53-58
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• 2002

In the construction of successful fuzzy models for nonlinear systems, the identification of an optimal fuzzy model system is an important and difficult problem. Traditionally, sGA(simple genetic algorithm) has been used to identify structures and parameters of fuzzy model because it has the ability to search the optimal solution somewhat globally. But SGA optimization process may be the reason of the premature local convergence when the appearance of the superior individual at the population evolution. Therefore, in this paper we propose a new method that can yield a successful fuzzy model using VmGA(virus messy genetic algorithms). The proposed method not only can be the countermeasure of premature convergence through the local information changed in population, but also has more effective and adaptive structure with respect to using changeable length string. In order to demonstrate the superiority and generality of the fuzzy modeling using VmGA, we finally applied the proposed fuzzy modeling methodof a complex nonlinear system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5624-5638
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• 2016

A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.342-348
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• 2009

This paper introduces a novel denoising algorithm for the partial-discharge(PD) signals from power apparatuses. The developed algorithm includes three kinds of specific denoising sub-algorithms. The first sub-algorithm uses the fuzzy logic which classifies the noise types in the magnitude versus phase PD pattern. This sub-algorithm is especially effective in the rejection of the noise with high and constant magnitude. The second one is the method simply removing the pulses in the phase sections below the threshold count in the count versus phase pattern. This method is effective in removing the occasional high level noise pulses. The last denoising sub-algorithm uses the grouping characteristics of PD pulses in the 3D plot of the magnitude versus phase versus cycle. This special technique can remove the periodical noise pulses with varying magnitudes, which are very difficult to be removed by other denoising methods. Each of the sub-algorithm has different characteristic and shows different quality of the noise rejection. On that account, a parameter which numerically expresses the noise possessing degree of signal, is defined and evaluated. Using the parameter and above three sub-algorithms, an adaptive complex noise rejection algorithm for the on-line PD diagnosis system is developed. Proposed algorithm shows good performances in the various real PD signals measured from the power apparatuses in the Korean plants.