Jang Kyeong Seon;Choi Chan Hun;Jeong Chan Won;Lee Yoon Ho;Yoon Yoo Sik;So Cheal Ho
Journal of Physiology & Pathology in Korean Medicine
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v.16
no.3
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pp.537-541
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2002
When a Kigong master concentrates the Qi at Yintang, Laogong(P8), Qihai(CV6) meridian points during Kigong state, the change of magnetic field around acupoints Yintang, Laogong points has been measured using DROS-SQUID apparatus. After smoothing process of the continuously measured magnetic signal around acupoints for a few minutes, we could observe that a series of peaks, magnitude of 1~2 pT and period of 5 sec, appeared and find that these peaks were clearly changed as if switch on and off according to Qi concentration state. Before Qi radiation, a series of the peaks measured on Yintang or Laogong point of a Kigong master shows one of either SW-ON state or SW-OFF state as initial state. During Qi radiation, its state becomes inverse of initial state. After Qi radiation, it returns to the initial state for some cases (called P type ; push button switch type) or it remains inversion state for other cases (called T type; toggle switch type). From the data of peaks measured at different position from the Qi concentration acupoint, we found that the Qi radiation on an acupoint makes the switching effect even not at the acupoint that Qi is concentrated but at the other acupoints that Qi is not concentrated.
Journal of the Institute of Electronics Engineers of Korea SC
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v.45
no.4
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pp.20-28
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2008
We propose a radial image processing method in a discrete polar coordinate system based on L1-norm. For this purpose, we first verified that the polar coordinate based on L2-norm can not exist in discrete system and then develop a method converting the Cartesian coordinate to the discrete polar coordinate. We apply the proposed method to smooth mass images of breast tissue and to detect the boundaries of extremely deformable objects. Compared to the Gaussian smoothing method performed in the Cartesian coordinate system, the proposed method stabilized the image signal while maintaining the overall radial shape of mass images. The proposed boundary detection method can detect shapes with high precision while conventional edge detectors can not accurately detect the shape of deformable objects. We also exploit the method to perform pupil detection and have had good experimental results.
In this paper, we propose a novel approach to improve the performance of minima controlled recursive averaging (MCRA) which is based on the conditional maximum a posteriori criterion. A crucial component of a practical speech enhancement system is the estimation of the noise power spectrum. One state-of-the-art approach is the minima controlled recursive averaging (MCRA) technique. The noise estimate in the MCRA technique is obtained by averaging past spectral power values based on a smoothing parameter that is adjusted by the signal presence probability in frequency subbands. We improve the MCRA using the speech presence probability which is the a posteriori probability conditioned on both the current observation the speech presence or absence of the previous frame. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and subjective evaluation of speech quality, we show that the proposed algorithm yields better results compared to the conventional MCRA-based scheme.
A signal passed through multi-path channel suffers ISI(Inter-Symbol Interference) and severe distortions caused by channel delay spread and noise components at the SC-FDE(Single Carrier with Frequency Domain Equalizer) transmission. Conventional UW(Unique-Word) based SC-FDE iterative channel estimation improves channel estimation performance by smoothing estimated CIR(Channel Impulse Response) of the noise components outside the channel length at time domain and restoring the broken cyclic property through UW reconstruction. In this paper, we propose channel estimation scheme through noise suppression within channel length. To suppress the noise, we estimate noise standard deviation as estimated CIR of the noise components outside the channel length and make criteria of the noise standard deviation gain that doesn't affect the original signal samples. When estimated CIR samples within channel length are less than the criteria value using the noise standard deviation and gain, the noise components are removed. Simulation results show that the proposed channel estimation scheme brings good channel MSE(Mean Square Error) and good BER(Bit Error Rate) performance.
For efficient use of wood, it is important to control moisture of wood in processing wood. Near-infrared (NIR) spectroscopy can be used to estimate the physical and chemical properties of materials quickly and nondestructively. In this study, it was intended to measure the moisture contents on the surface of wood using NIR spectroscopy coupled with multivariate analytic statistical techniques. Because NIR spectroscopy is affected by the chemical components of the specimens and contains signal noise, a regression model for detecting moisture content of wood was established after carrying out several numerical pretreatments such as Smoothing, Derivative and Normalization in this study. It shows that the regression model using NIR absorbance in the range of 750~2,500 nm predicts the actual surface moisture content very well. Near-infrared spectroscopy technique developed in this study is expected to improve a technology to control moisture content of wood in using and drying process.
We obtained precise linear transverse displacements from the results of signal processing on moire fringes measured by the superposition of a fixed self-imaging elongated circular(EC) grating and a moved EC grating. The linear displacement less than one pitch of the moving EC grating was calculated from the position of a bright moire fringe generated on the linear grating part of the EC gratings. The moire signals were high-frequency-filtered, smoothed, curve-fitted, and first-differentiated moire signals in sequence. Also the linear displacement created by movement by the unit of integer times of a pitch was readily measured by the count of the even number of zero-crossing points corresponding to bright moire fringes obtained by the above same processing without curve fitting. Then we can measure linear transverse displacements with the accuracy of better than 3 %, which are more accurate values than those by the traditional visual method within the displacement of 80 ${\mu}{\textrm}{m}$.
Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$$Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.
For gas hydrate exploration, long offset multichannel seismic data acquired using by the 4km streamer length in Ulleung basin of the East Sea. The dataset was processed to define the BSRs (Bottom Simulating Reflectors) and to estimate the amount of gas hydrates. Confirmation of the presence of Bottom Simulating reflectors (BSR) and investigation of its physical properties from seismic section are important for gas hydrate detection. Specially, faster interval velocity overlying slower interval velocity indicates the likely presences of gas hydrate above BSR and free gas underneath BSR. In consequence, estimation of correct interval velocities and analysis of their spatial variations are critical processes for gas hydrate detection using seismic reflection data. Using Dix's equation, Root Mean Square (RMS) velocities can be converted into interval velocities. However, it is not a proper way to investigate interval velocities above and below BSR considering the fact that RMS velocities have poor resolution and correctness and the assumption that interval velocities increase along the depth. Therefore, we incorporated Migration Velocity Analysis (MVA) software produced by Landmark CO. to estimate correct interval velocities in detail. MVA is a process to yield velocities of sediments between layers using Common Mid Point (CMP) gathered seismic data. The CMP gathered data for MVA should be produced after basic processing steps to enhance the signal to noise ratio of the first reflections. Prestack depth migrated section is produced using interval velocities and interval velocities are key parameters governing qualities of prestack depth migration section. Correctness of interval velocities can be examined by the presence of Residual Move Out (RMO) on CMP gathered data. If there is no RMO, peaks of primary reflection events are flat in horizontal direction for all offsets of Common Reflection Point (CRP) gathers and it proves that prestack depth migration is done with correct velocity field. Used method in this study, Tomographic inversion needs two initial input data. One is the dataset obtained from the results of preprocessing by removing multiples and noise and stacked partially. The other is the depth domain velocity model build by smoothing and editing the interval velocity converted from RMS velocity. After the three times iteration of tomography inversion, Optimum interval velocity field can be fixed. The conclusion of this study as follow, the final Interval velocity around the BSR decreased to 1400 m/s from 2500 m/s abruptly. BSR is showed about 200m depth under the seabottom
The digital data were obtained using Kennedy 9000 magnetic tape deck which was connected to the SMS960 side scan sonar during the field operations. The data of three consecutive survey tracks near Seongsan-po, Cheju were used for the development of this study. The softwares were mainly written in Fortran-77 using VAX 11/780 MINI-COMPUTER (CPU Memory; 4MB). The established mapping system consists of the pretreatment and the digital processing of seafloor image data. The pretreatment was necessary because the raw digital data format of the field magnetic tapes was not compatible to the VAX system. Therefore the raw data were read by the personal computer using the Assembler language and the data format was converted to IBM compatible, and next data were communicated to the VAX system. The digital processing includes geometrical correction for slant range, statistical analysis and cartography of the seafloor image. The sound speed in the water column was assumed 1,500 m/sec for the slant range correction and the moving average method was used for the signal trace smoothing. Histograms and cumulative curves were established for the statistical analysis, that was purposed to classify the backscattering strength from the sea-bottom. The seafloor image was displayed on the color screen of the TEKTRONIX 4113B terminal. According to the brief interpretation of the result image map, rocky and sedimentary bottoms were very well discriminated. Also it was shown that the backscattered acoustic pressurecorrelateswith the grain size and sorting of surface sediments.
The Journal of Korean Institute of Communications and Information Sciences
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v.34
no.11A
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pp.882-890
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2009
In this paper, we describe a compensation method that can be used for the situation where Loran receivers lose their phase lock to the received Loran signals when Loran signals are employed for the synchronization of national infrastructures such as telecommunication networks, electric power distribution and so on. In losing the phase lock to the received signals in a Loran receiver, the inner oscillator of the receiver starts free-running and the performance of the timing synchronization signals which are locked to the oscillator's phase is very severly degraded, so the timing accuracy under 1 us for a Primary Reference Clock (PRC) required in the International Telecommunications Union (ITU) G.811 standard can not be satisfied in the situation. Therefore, in this paper, we propose a method which can compensate the phase jump by using a compensation algorithm when a Loran receiver loses its phase lock and the performance evaluation of the proposed algorithm is achieved by the Maximum Time Interval Error (MTIE) of the measured data. From the performance evaluation results, it is observed that the requirement under 1 us for a PRC can be easily achieved by using the proposed algorithm showing about 0.6 us with under 30 minutes mean interval of smoothing with 1 hour period when the loss of phase lock occurs.
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