• Proceedings of the KSPS conference
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• 2003.05a
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• pp.211-214
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• 2003

일반적으로 음성 인식에서의 성능은 잡음의 영향으로 인하여 저하된다. 전화망을 통한 한국어 연속 숫자음 인식은 음성인식 분야에 있어서 어려운 영역에 속하는데, 이는 조음 현상으로 인한 인식률 저하되는 점과 전화망 채널의 영향으로 인하여 스펙트럼 포락이 왜곡되며 음성신호의 대역폭이 제한되기 때문이다. 본 논문에서는 잡음의 영향을 줄이기 위하여, 2WF(2-stage Wiener Filter) 와 SWP (SNR-dependent Waveform Processing) 그리고 CMN(Cepstrum Mean Normalization)을 사용하였다. 2WF는 음성 신호의 포만트 구조를 적게 왜곡시키면서 전체적인 가산잡음 뿐만 아니라 동적 가산잡음도 줄여준다. SWP는 음성파형에서 SNR값이 상대적으로 큰 부분을 강조하여 전체적인 SNR을 향상시킬 수 있다. 또한, CMN은 특징벡터로부터 채널잡음의 영향을 정규화하여 음성 인식 성능을 향상시킨다. 이러한 방법들을 전화망 한국어 연속 숫자음 DB를 이용하여 실험한 결과, 음성신호의 왜곡을 최소화하면서 잡음의 영향을 줄여 전화망에서의 숫자음 인식 성능을 향상시킬 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.529-535
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• 2011

After permission for utilization of TV white space by FCC, a lot of attentions are focused on spectrum sensing, and various spectrum sensing methods have been proposed. However, they do not consider real environment, thus they are hard to achieve the required performance. In this paper, we propose resolutions for the problem which could be occurred in implementation of spectrum sensing module and verify performance of the proposed methods with computer simulation. The first proposed method utilizes channel status information to separate received signal and spurious for reducing false alarm probability caused by system internal spurious. The another proposed scheme is subband normalization method to prevent miss detection caused by multiple narrow band signals with different received signal strength. The simulation results verify that we can prevent false alarm cause by spurious components with the proposed system internal spurious cognition. Moreover, the proposed subband normalization method shows that it could overcome performance degradation caused by received signal strength difference.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.603-611
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• 2003

This paper proposes an effective feature compensation scheme based on speech model for achieving robust speech recognition. Conventional model-based method requires off-line training with noisy speech database and is not suitable for online adaptation. In the proposed scheme, we can relax the off-line training with noisy speech database by employing the parallel model combination technique for estimation of correction factors. Applying the model combination process over to the mixture model alone as opposed to entire HMM makes the online model combination possible. Exploiting the availability of noise model from off-line sources, we accomplish the online adaptation via MAP (Maximum A Posteriori) estimation. In addition, the online channel estimation procedure is induced within the proposed framework. For more efficient implementation, we propose a selective model combination which leads to reduction or the computational complexities. The representative experimental results indicate that the suggested algorithm is effective in realizing robust speech recognition under the combined adverse conditions of additive background noise and channel distortion.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.58-65
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• 2016

This paper presents optimization techniques to reduce the processing time of the dehazing method and proposes an efficient dehazing method based on them. In the proposed techniques, the atmospheric light is estimated based on the distributed sorting of the dark channel pixels, so as to reduce the computations. The normalization process required in the transmission estimation is simplified by the assumption that the atmospheric light is monochromatic. In addition, the dark channel is modified into the median dark channel in order to eliminate the transmission refinement process while achieving a comparable dehazing quality. The proposed dehazing method based on the optimization techniques is presented and its performance is investigated by developing a prototype system. When compared to the previous method, the proposed dehazing method reduces the processing time by 65% while maintaining the dehazing quality.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.2 s.332
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• pp.61-74
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• 2005

Digital Multimedia Broadcasting(DMB) is a reliable multi-service system for reception by mobile and portable receivers. DMB system allows interference-free reception under the conditions of multipath propagation and transmission errors using COFDM modulation scheme, simultaneously, needs powerful channel error's correction ability. Viterbi Decoder for DMB receiver uses punctured convolutional code and needs lots of computations for real-time operation. So, it is desired to design a high speed and low-power hardware scheme for Viterbi decoder. This paper proposes a combined add-compare-select(ACS) and path metric normalization(PMN) unit for computation power. The proposed PMN architecture reduces the problem of the critical path by applying fixed value for selection algorithm due to the comparison tree which has a weak point from structure with the high-speed operation. The proposed ACS uses the decomposition and the pre-computation technique for reducing the complicated degree of the adder, the comparator and multiplexer. According to a simulation result, reduction of area $3.78\%$, power consumption $12.22\%$, maximum gate delay $23.80\%$ occurred from punctured viterbi decoder for DMB system.

• Journal of Pharmaceutical Investigation
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• v.26 no.1
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• pp.33-41
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• 1996

In order to study the effect of phenobarbital(PB) on the hepatic transport of diltiazem(DTZ), $Ca^{2+}$ channel blocker, we used isolated hepatocytes of rat which was intraperitoneally pretreated with phenobarbital sodium(75 mg/kg) for four days once a day. For the isolation of rat liver cells, a modification of the two step procedure of Seglen was used. DTZ was dissolved in incubation buffer to the final DTZ concentrations of 200, 400, 600, 800 and 1000 ng/ml in order to elucidate the uptake characteristics of DTZ by hepatocytes. Reactions were stopped at 10, 20, 30, 45, 60, 90, 120 and 300 sec. The initial velocity was determined by disappearance of diltiazem in the hepatocyte suspension. On the other hand, to determine the effect of PB on the in vitro hepatic intrinsic clearance of DTZ we obtained the metabolism rates of DTZ in the control and the PB-pretreated rat hepatocyte at various time intervals. According to pretreatment with PB, the size of hepatocyte and the amount of protein per $10^6$ cells were significantly (p<0.01) increased from $26.92{\pm}0.1364\;m$ to $35.31{\pm}1.00\;m$ and from $468{\pm}6.5\;{\mu}g/10^6$ cells to $628.8{\pm}12.1{\mu}g/10^6$ cells, respectively. In the case or hepatic uptake of diltiazem, $K_m$ was not different in the normalization by cell numbers and increased from $2.90\;{\mu}M\;to\;13.89\;{\mu}M$ in the normalization by protein amount. $V_max$ was increased regardless of normalization by protein amount and cell numbers, from $1.21\;{\mu}mole/min \;{\cdot}\;mg\;protein\;to\;3.96\;{\mu}mole/min\;{\cdot}\;mg\;protein\;and\;from\;2.38\;{\mu}mole/min\;{\cdot}\;10^6\;cells\;to\;2.83\;{\mu}mole/min\;{\cdot}\;10^6\;cells$, respectively. The in vitro hepatic intrinsic clearance of DTZ was significantly (p<0.01) increased from $0.640{\pm}0.038\;ml/mim\;{\cdot}\;10^6\;cells\;to\;2.385{\pm}0.212\;ml/min\;{\cdot}\;10^6\;cells$ due to PB-pretreatment. These results suggest that the uptake of DTZ by hepatocyte is extremely fast and PB enhances the hepatic intrinsic metabolic clearance of DTZ.

• Progress in Superconductivity
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• v.5 no.2
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• pp.98-104
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• 2004

We analyzed a noise-sensitivity profile of a specific SQUID sensor system for the localization of brain activity. The location of a neuromagnetic current source is estimated from the recording of spatially distributed SQUID sensors. According to the specific arrangement of the sensors, each site in the source space has different sensitivity, that is, the difference in the lead field vectors. Conversely, channel noises on each sensor will give a different amount of the estimation error to each of the source sites. e.g., a distant source site from the sensor system has a small lead-field vector in magnitude and low sensitivity. However, when we solve the inverse problem from the recorded sensor data, we use the inverse of the lead-field vector that is rather large, which results in an overestimated noise power on the site. Especially, the spatial sensitivity profile of a gradiometer system measuring tangential fields is much more complex than a radial magnetometer system. This is one of the causes to make the solutions of inverse problems unstable on intervening of the sensor noise. In this study, in order to improve the localization accuracy, we calculated the noise-sensitivity profile of our 40-channel planar SQUID gradiometer system, and applied it as a normalization weight factor to the source localization using synthetic aperture magnetometry.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.569-580
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• 2012

In this paper, an enhanced initial ranging algorithm for large-cell coverage fixed wireless communication system is proposed. In typical wireless communication system such as WiBro, because a round-trip delay between a transmitter and a receiver is within one OFDM (Orthogonal Frequency Division Multiplexing) symbol duration, a frequency-domain differential correlation method is generally used. However, the conventional method cannot be applied due to an increase of a maximum time delay in large-cell system. In case of an accumulative differential method, estimation errors can occur because of frequent sign transitions. In this paper, therefore, we propose an algorithm which can estimate a total timing offset in a ranging channel structure for 15 km cell. The proposed method can improve performance by sign comparison based sign error correction rule between the estimated values and using a weighting scheme based on channel correlation, the number of accumulations, and the noise reduction effect in normalization process. Also, it can estimate the integer timing offset of symbol duration by comparing peak-powers after compensating for the fractional timing offset of symbol duration.

• Korean Journal of Pharmacognosy
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• v.36 no.1 s.140
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• pp.17-20
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• 2005

We previously reported that the exogenous administration of cumambrin A, a sesquiterpene lactone from the dried flowers of Chrysanthemum boreale Makino has a pharmacological effect on normalization of blood pressure in the spontaneously hypertensive rats (SHR). In the present study, we further investigated the effect of cumambrin A on the relaxation of phenylephrine-induced precontracted rat aortic artery rings. The potency of cumambrin A was than compared to verapamil, a well known $Ca^{2+}-channel$ blocker. The results demonstrate that the isolated rat aortic arteries are relaxed to basal tension at a concentration of $5{\times}10^{-5}\;M$ cumambrin A treatment. The results also show that the phenylephrine-induced contraction is inhibited by a pretreatment of cumambrin A. Co-treatment of cumambrin A and verapamil showed a strong synergetic effect on the relaxation of rat aortic artery rings. Thus, these data demonstrate that cumambrin A is a potent relaxant of rat aortic smooth muscle and suggest that cumambrin A modulates intracellular or extracellular $Ca^{2+}$ mobilization.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.1025-1032
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• 2020

In this paper, we propose a method to classify road weather conditions into rain, fog, and sun using a SVM (Support Vector Machine) classifier after extracting weather features from images acquired in real time using an optical sensor installed on a roadside post. A multi-dimensional weather feature vector consisting of factors such as image sharpeness, image entropy, Michelson contrast, MSCN (Mean Subtraction and Contrast Normalization), dark channel prior, image colorfulness, and local binary pattern as global features of weather-related images was extracted from road images, and then a road weather classifier was created by performing machine learning on 700 sun images, 2,000 rain images, and 1,000 fog images. Finally, the classification performance was tested for 140 sun images, 510 rain images, and 240 fog images. Overall classification performance is assessed to be applicable in real road services and can be enhanced further with optimization along with year-round data collection and training.