Journal of the Institute of Electronics Engineers of Korea CI
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v.37
no.1
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pp.1-10
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2000
In this paper, a new digital watermarking algorithm using wavelet transform is proposed. Wavelet transform is widely used for image processing, because of its multiresolution characteristic which conforms to the principles of the human visual system(HVS). It is also very efficient for localizing images in the spatial and frequency domain. Since wavelet coefficients can be characterized by the gaussian distribution, the proposed algorithm uses a gaussian distributed random vector as the watermark in order to achieve invisibility and robustness. After the original image is transformed using DWT(Discrete Wavelet Transform), the coefficients of all subbands including LL subband are utilized to equally embed the watermark to the whole image. To select perceptually significant coefficients for each subband, we use level-adaptive thresholding. The watermark is embedded to the selected coeffocoents, using different scale factors according to the wavelet characteristics. In the process of watermark detection, the similarity between the original watermark and the extracted watermark is calculated by using vector projection method. We analyze the performance of the proposed algorithm, compared with other transform-domain watermarking methods. The experimental results tested on various images show that the proposed watermark is less visible to human eyes and more robust to image compressions, image processings, geometric transformations and various noises, than the existing methods.
Journal of the Institute of Electronics and Information Engineers
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v.51
no.6
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pp.102-109
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2014
A particle system is used for modeling the physical phenomenon. There are many traditional ways for simulation modeling which can be well suited for application including the landscapes of branches, clouds, waves, fog, rain, snow and fireworks in the three-dimensional space. In this paper, we present a new fireworks modeling technique for modeling 3D firework based on Firework Particle Tracking (FPT) using the particle system. Our method can track and recognize the launched and exploded particle of fireworks, and extracts relatively accurate 3D positions of the particles using 3D depth values. It can realize 3D simulation by using tracking information such as position, speed, color and life time of the firework particle. We exploit Region of Interest (ROI) for fast particle extraction and the prevention of false particle extraction caused by noise. Moreover, Kalman filter is used to enhance the robustness in launch step. We propose a new fireworks particle tracking method for the efficient tracking of particles by considering maximum moving range and moving direction of particles, and shall show that the 3D speeds of particles can be obtained by finding the rotation angles of fireworks. Also, we carry out the performance evaluation of particle tracking: tracking speed and accuracy for tracking, classification, rotation angle respectively with respect to four types of fireworks: sphere, circle, chrysanthemum and heart.
Journal of the Institute of Electronics Engineers of Korea CI
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v.39
no.2
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pp.45-53
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2002
A wavelet-based digital watermarking algorithm is proposed that uses the successive subband quantization and human visual system (HVS). After an original image is decomposed into 4-level by the discrete wavelet transform, perceptually significant coefficients (PSC) of each subband excluding the lowest level subband are utilized to embed the watermark. PSC of the baseband ate chosen according to their amplitude and they are slightly modified to embed the watermark by a conventional embedding method. By the successive subband quantization, PSC of the high frequency subband are chosen and slightly modified according to the HVS. We tested the performance of the proposed algorithm compared with the conventional watermarking algorithm by computer simulation. Experimental results show that the proposed watermarking algorithm produces a better invisibility and robustness than the conventional algorithm.
A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.
In this paper, a new automatic speech recognition (ASR) was proposed where ultrasonic doppler signals were used, instead of conventional speech signals. The proposed method has the advantages over the conventional speech/non-speech-based ASR including robustness against acoustic noises and user comfortability associated with usage of the non-contact sensor. In the method proposed herein, 40 kHz ultrasonic signal was radiated toward to the mouth and the reflected ultrasonic signals were then received. Frequency shift caused by the doppler effects was used to implement ASR. The proposed method employed multi-channel ultrasonic signals acquired from the various locations, which is different from the previous method where single channel ultrasonic signal was employed. The PCA(Principal Component Analysis) coefficients were used as the features of ASR in which hidden markov model (HMM) with left-right model was adopted. To verify the feasibility of the proposed ASR, the speech recognition experiment was carried out the 60 Korean isolated words obtained from the six speakers. Moreover, the experiment results showed that the overall word recognition rates were comparable with the conventional speech-based ASR methods and the performance of the proposed method was superior to the conventional signal channel ASR method. Especially, the average recognition rate of 90 % was maintained under the noise environments.
The most important factor influencing the robustness of the Internet Is the end-to-end TCP congestion control. However, the congestion control scheme of TCP Reno, the most popular TCP version on the Internet, employs passive congestion indication. It makes worse the network congestion. Recently, Brakmo and Peterson have proposed a new version of TCP, which is named TCP Vegas, with a fundamentally different congestion control scheme from that of the Reno. Many studies indicate that the Vegas is able to achieve better throughput and higher stability than the Reno. But there are two unfairness problems in Vegas. These problems hinder the spread of the Vegas in current Internet. In this paper, in order to solve these unfairness problems, we propose a new congestion control algorithm called TCP PowerVegas. The existing Vegas depends mainly only on the rtt(round trip time), but the proposed PowerVegas use the new congestion control scheme combined the Information on the rtt with the information on the packet loss. Therefore the PowerVegas performs the congestion control more competitively than the Vegas. Thus, the PowerVegas is able to solve effectively these unfairness problems which the Vegas has experienced. To evaluate the proposed approach, we compare the performance among PowerVegas, Reno and Vegas under same network environment. Using simulation, the PowerVegas is able to achieve better throughput and higher stability than the Reno and is shown to achieve much better fairness than the existing Vegas.
Major deficiencies of current automation scheme including various robots for bioproduction include the lack of task adaptability and real time processing, low job performance for diverse tasks, and the lack of robustness of take results, high system cost, failure of the credit from the operator, and so on. This paper proposed a scheme that could solve the current limitation of task abilities of conventional computer controlled automatic system. The proposed scheme is the man-machine hybrid automation via tele-operation which can handle various bioproduction processes. And it was classified into two categories. One category was the efficient task sharing between operator and CCM(computer controlled machine). The other was the efficient interface between operator and CCM. To realize the proposed concept, task of the object identification and extraction of 3D coordinate of an object was selected. 3D coordinate information was obtained from camera calibration using camera as a measurement device. Two stereo images were obtained by moving a camera certain distance in horizontal direction normal to focal axis and by acquiring two images at different locations. Transformation matrix for camera calibration was obtained via least square error approach using specified 6 known pairs of data points in 2D image and 3D world space. 3D world coordinate was obtained from two sets of image pixel coordinates of both camera images with calibrated transformation matrix. As an interface system between operator and CCM, a touch pad screen mounted on the monitor and remotely captured imaging system were used. Object indication was done by the operator’s finger touch to the captured image using the touch pad screen. A certain size of local image processing area was specified after the touch was made. And image processing was performed with the specified local area to extract desired features of the object. An MS Windows based interface software was developed using Visual C++6.0. The software was developed with four modules such as remote image acquisiton module, task command module, local image processing module and 3D coordinate extraction module. Proposed scheme shoed the feasibility of real time processing, robust and precise object identification, and adaptability of various job and environments though selected sample tasks.
In many continuous speech recognition systems based on HMMs, decision tree-based state tying has been used for not only improving the robustness and accuracy of context dependent acoustic modeling but also synthesizing unseen models. To construct the phonetic decision tree, standard method performs one-level pruning using just single Gaussian triphone models. In this paper, two novel approaches, two-level decision tree and multi-mixture decision tree, are proposed to get better performance through more accurate acoustic modeling. Two-level decision tree performs two level pruning for the state tying and the mixture weight tying. Using the second level, the tied states can have different mixture weights based on the similarities in their phonetic contexts. In the second approach, phonetic decision tree continues to be updated with training sequence, mixture splitting and re-estimation. Multi-mixture Gaussian as well as single Gaussian models are used to construct the multi-mixture decision tree. Continuous speech recognition experiment using these approaches on BN-96 and WSJ5k data showed a reduction in word error rate comparing to the standard decision tree based system given similar number of tied states.
Purpose: Corporate social responsibility is a self-regulating business model that helps a firm be socially accountable to the public. By practicing corporate social responsibility, firms can be conscious of the kind of impact they are having on all aspects of society, including economic, social, and environmental. Corporate social responsibility activities are not directly linked to increasing corporate performance and corporate value, but rather involve spending expenses. Based on these facts, this study verifies whether the effects of corporate social responsibility activities differ depending on the firm's situation. Research design, data and methodology: This study analyzed the effect of market competition on corporate social responsibility activities using logistic regression analysis on listed companies in the KOSPI and KOSDAQ for fiscal years 2014 through 2016. In this study, market competition was measured using the Herfindahl-Herschman Index(HHI). Higher HHI value can be interpreted as a lower degree of market competition. We also measured corporate social responsibility activities using the KEJI Index published by the Korea Economic Justice Institute (KEJI). If a firm-year is included in the top 200 companies of the KEJI Index, it is classified as a good corporate social responsibility activity firm. Results: We find that companies in less competitive market were not included in the KEJI Index. This result indicates that firms in the market with lower market competition perform less corporate social responsibility activities that incur costs. An additional analysis showed that there was a significant negative relationship between the market competition and the corporate social responsibility activity scores published by the KEJI Index. These result adds robustness to the result of the hypothesis that firms that have a monopolistic place in the market practice passive corporate social responsibility activities. Conclusions: The results show that managers of a firm in the lower market competition have a lower incentive to use limited resources for projects that are not directly related to revenue. The results of this study imply that corporate social responsibility activities vary according to the position of the business. Therefore, this study suggests that market investors should consider the degree of competition in the market when they evaluate corporate social responsibility activities.
Journal of the Korean Institute of Telematics and Electronics T
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v.35T
no.1
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pp.90-98
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1998
This paper is to describe the improved vector control which can control the induction motor robustly in low speed. When the induction motor is drived with low speed, below 10 percent of the rated speed, an algorithm which can compensate the error of unit vector angle generated by the harmonics is proposed. Another algorithm which can be tuned to the rotor time constant so that nay be robust to the rotor parameter change in low speed and transient state was proposed. The ripple of flux and torque was reduced by the proposed vector control and then the stable output characteristics was obtained in low speed. When the input and output is sinusoidal, the proposed vector control, the direct vector control and the indirect vector control were analyzed and compared in the low speed characteristics. And each control characteristics is compared and analyzed in state of containing harmonics. The estimation and tunning performance of rotor time constant is confirmed with simulation. The whole control system is implemented by real hardware and experimented to compare the proposed vector control with the direct vector control. As a result of the experiment with two control methods in low speed, the torque ripple of the proposed vector control is improved by 45 percent than the direct vector control. And it is confirmed that the flux current ripple is reduced in 0.2 p.u. and torque current ripple is reduced in 0.6 p.u. It is confirmed that the rotor time constant by the estimation and the tunning algorithm is tunned by the real rotor time constant. Finally, it was confirmed that the validity and robustness for the proposed vector control in low speed existed.
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