• Molecules and Cells
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• 제27권6호
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• pp.681-687
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• 2009

We examined the effects of synthetic signal peptides, wild-type (WT) and export-defective mutant (MT) of ribose-binding protein, on the conformational changes of signal recognition particle 54 homologue (Ffh) in Escherichia coli. Upon interaction of Ffh with WT peptide, the intrinsic Tyr fluorescence, the transition temperature of thermal unfolding, and the GTPase activity of Ffh decreased in a peptide concentration-dependent manner, while the emission intensity of 8-anilinonaphthalene-1-sulfonic acid increased. In contrast, the secondary structure of the protein was not affected. Additionally, polarization of fluorescein-labeled WT increased upon association with Ffh. These results suggest that WT peptide induces the unfolded states of Ffh. The WT-mediated conformational change of Ffh was also revealed to be important in the interaction between SecA and Ffh. However, MT had marginal effect on these conformational changes suggesting that the in vivo functionality of signal peptide is important in the interaction with Ffh and concomitant structural change of the protein.

• 전기학회논문지
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• 제59권4호
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• pp.779-787
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• 2010

In this paper, We introduce electrical tracking generated from surface activity associated with flow of leakage current on insulator under wet and contaminated conditions and design electrical tracking pattern recognition system by using LabVIEW. We measure the leaking current of contaminated wire by using LabVIEW software and the NI-c-DAQ 9172 and NI-9239 hardware. As pattern recognition algorithm and optimization algorithm for electrical tracking system, neural networks, Radial Basis Function Neural Networks(RBFNNs) and particle swarm optimization are exploited. The designed electrical tracking recognition system consists of two parts such as the hardware part of electrical tracking generator, the NI-c-DAQ 9172 and NI-9239 hardware and the software part of LabVIEW block diagram, LabVIEW front panel and pattern recognition-related application software. The electrical tracking system decides whether electrical tracking generate or not on electrical wire.

• 한국군사과학기술학회지
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• 제26권2호
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• pp.122-128
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• 2023

The target must be located within the main-lobe of the antenna in order to measure the direction of the target by using sum-delta monopulse technique. The most common way if the target is located within the main-lobe is to compare the amplitude of the sum channel received signal with the delta channel received signal. However, in the case of the single-ring circular array antenna, it is difficult to apply the conventional method due to its structural limitation where antenna elements do not exist in the center of the array. In this paper, we proposed a novel method to identify whether a target is located within the main-lobe by appropriately adjusting the feeding amplitude of each element constituting the single-ring circular array antenna through the particle swarm optimization method. Simulation results showed that the proposed method can determine whether the target is located within the main-lobe of the single-ring circular array antenna.

• 한국생물물리학회:학술대회논문집
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• 한국생물물리학회 1999년도 학술발표회 진행표 및 논문초록
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• pp.43-43
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• 1999

Signal peptides of secretary proteins interact with various membranes and non-membrane components during the translocation. We investigated the interaction of signal peptides of ribose binding protein (RBP) with Escherichia coli (E.coli) signal recognition particle (SRP), SecA and lipid bilayer. Previous studies showed that the functional signal peptides inhibit the GTPase activity of E.coli SRP which consisted of F로 and 4.5S RNA.(omitted)

• ETRI Journal
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• 제35권5호
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• pp.869-879
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• 2013

This study is related to the acquisition of physiological signals of human emotions and the recognition of human emotions using such physiological signals. To acquire physiological signals, seven emotions are evoked through stimuli. Regarding the induced emotions, the results of skin temperature, photoplethysmography, electrodermal activity, and an electrocardiogram are recorded and analyzed as physiological signals. The suitability and effectiveness of the stimuli are evaluated by the subjects themselves. To address the problem of the emotions not being recognized, we introduce a methodology for a recognizer using prototype-based learning and particle swarm optimization (PSO). The design involves two main phases: i) PSO selects the P% of the patterns to be treated as prototypes of the seven emotions; ii) PSO is instrumental in the formation of the core set of features. The experiments show that a suitable selection of prototypes and a substantial reduction of the feature space can be accomplished, and the recognizer formed in this manner is characterized by high recognition accuracy for the seven emotions using physiological signals.

• The Journal of the Acoustical Society of Korea
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• 제28권3E호
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• pp.109-117
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• 2009

Identity recognition in real environment with a reliable mode is a key issue in human computer interaction (HCI). In this paper, we present a robust person identification system considering score-based optimal reliability measure of audio-visual modalities. We propose an extension of the modified reliability function by introducing optimizing parameters for both of audio and visual modalities. For degradation of visual signals, we have applied JPEG compression to test images. In addition, for creating mismatch in between enrollment and test session, acoustic Babble noises and artificial illumination have been added to test audio and visual signals, respectively. Local PCA has been used on both modalities to reduce the dimension of feature vector. We have applied a swarm intelligence algorithm, i.e., particle swarm optimization for optimizing the modified convection function's optimizing parameters. The overall person identification experiments are performed using VidTimit DB. Experimental results show that our proposed optimal reliability measures have effectively enhanced the identification accuracy of 7.73% and 8.18% at different illumination direction to visual signal and consequent Babble noises to audio signal, respectively, in comparison with the best classifier system in the fusion system and maintained the modality reliability statistics in terms of its performance; it thus verified the consistency of the proposed extension.

• 미생물학회지
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• 제39권3호
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• pp.135-140
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• 2003

Bacillus sp.는 다량의 효소와 기능성 펩타이드들을 세포외로 분비하는 것으로 알려져 있다. Signal recognition particle (SRP)과 SRP receptor는 세포외 분비 단백질의 이동에 있어서 중심적 역할을 담당한다. B. lentimorbus WJ5의 DNA microarray 결과, 감마선 조사로 유도된 항진균 활성 결핍 돌연변이체인 WJ5m12에서 B. subtilis srb homologue (srbL)의 발현이 감소되는 것을 관찰할 수 있었다. SRP receptor와 항진균 활성 사이의 연관성을 고찰하기 위하여 B. lentimorbus WJ5의 srbL을 PCR로 증폭하여 pQE30 vector에 클로닝 하였으며, B. lentimorbus WJ5m12에 형질전환 시켰다. 형질전환된 B. lentimorbus WJ5m12::srbL은 항진균 활성이 복원되었다. 이차원 전기영동 결과, 수 종의 세포외 분비 단백질의 전구체들이 항진균 활성 결핍 돌연변이 균주에서 축적되었고 B.lentimorbus WJ5m12::srbL에서는 야생형 균주의 단백질 수준까지 감소되는 현상을 관찰할 수 있었다. 이는 B.lentimorbus WJ5의 항진균 활성 관련 물질의 이동에 있어서 srbL이 중요한 역할을 한다는 것을 암시한다.

• 미생물학회지
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• 제39권3호
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• pp.141-147
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• 2003

여러 항진균 활성 관련 유전자들의 발현 수준을 동시에 연구하기 위하여 DNA microarray를 이용하여 유전자들의 발현 패턴을 비교 분석하였다. 본 연구에서는 항진균활성을 가지는Bacillus lentimorbus WJ5의 genomic DNA를 무작위 하게 제한효소로 절단하여 2,000개의 DNA단편을 microarray하였으며, 감마선($^{60}Co$)조사로 유도된 7종의 항진균 활성 결핍 돌연변이체와 발현양상을 정량적으로 비교하였다. Gene Cluster (Michael Risen, Stanford Uniy.)를 이용한 DNA microarray의 분석 결과, 총 408개의 DNA 단편이 발현되는 것을 확인할 수 있었으며, 이들 중 20개의 DNA단편이 항진균 활성 결핍 돌연변이체에서 발현이 억제되는 것으로 나타났다. 특히,pbuX (xanthine permease, K222), ywbA (phosphotransferase system enzyme II, K393), ptsG (PTS glucose specific enzyme II ABC component, K877), yufO (ABC transporter(ATP-binding protein), K1301), 그리고 ftsY (signal recognition particle (docking protein), K868)는 모든 돌연변이체에서 동시에 발현되는 down-regulation된 유전자들로서 물질 이동과 관련된 것으로 보고되어 있으며, 항진균 활성 관련 신호 및 물질의 이동에 관여할 것으로 사료되어진다.

• 대한음성학회지:말소리
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• 제64호
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• pp.121-135
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• 2007

Speech signal is distorted by channel characteristics or additive noise and then the performances of speaker or speech recognition are severely degraded. To cope with the noise problem, we propose a modified HMM decoder algorithm using SNR-based observation confidence, which was successfully applied for GMM in speaker identification task. The modification is done by weighting observation probabilities with reliability values obtained from SNR. Also, we apply PSO (particle swarm optimization) method to the confidence function for maximizing the speaker identification performance. To evaluate our proposed method, we used the ETRI database for speaker recognition. The experimental results showed that the performance was definitely enhanced with the modified HMM decoder algorithm.

• 대한임베디드공학회논문지
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• 제15권3호
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• pp.119-127
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• 2020

The detection and recognition of abnormal driving becomes crucial for achieving safety in Intelligent Transportation Systems (ITS). This paper presents a feature extraction method based on spectral data to train a neural network model for driving behavior recognition. The proposed method uses a two stage signal processing approach to derive time-saving and efficient feature vectors. For the first stage, the feature vector set is obtained by calculating variances from each frequency bin containing the power spectrum data. The feature set is further reduced in the second stage where an intersection method is used to select more significant features that are finally applied for training a neural network model. A stream of live signals are fed to the trained model which recognizes the abnormal driving behaviors. The driving behaviors considered in this study are weaving, sudden braking and normal driving. The effectiveness of the proposed method is demonstrated by comparing with existing methods, which are Particle Swarm Optimization (PSO) and Convolution Neural Network (CNN). The experiments show that the proposed approach achieves satisfactory results with less computational complexity.