• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.11 no.7
• /
• pp.287-294
• /
• 2001

The identification of connection stiffnesses of bolted structures is presented using FRT-based substructural sensitivity analysis. The substructural design sensitivity formula is derived and plugged into the optimization module of MATLAB to identify connection stiffnesses of an air-conditioner compressor or passenger Car. The air-conditioner composed of a compressor and a bracket, is analysed by using the FRT-based substructural(FBS) method to obtain FTRs an FE model is generated for the bracket, and the impact hammer test is performed for the compressor, Obtained FRTs are combined to calculate the reaction force at the connection point and the system response. By minimizing the difference between a target FRT and calculated one the connection element properties of the air-conditioner syste are identified It is shown that the proposed identification method is effective for a real problem.

• Speech Sciences
• /
• v.7 no.3
• /
• pp.185-195
• /
• 2000

This paper seeks to compare the feature parameters used in speaker identification systems under noisy environments. The feature parameters compared are LP cepstrum (LPCC), Cepstral mean subtraction(CMS), Pole-filtered CMS(PFCMS), Adaptive component weighted cepstrum(ACW) and Postfilter cepstrum(PF). The GMM-based text independent speaker identification system is designed for this target. Some series of experiments show that the LPCC parameter is adequate for modelling the speaker in the matched environments between train and test stages. But in the mismatched training and testing conditions, modified parameters are preferable the LPCC. Especially CMS and PFCMS parameters are more effective for the microphone mismatching conditions while the ACW and PF parameters are good for more noisy mismatches.

• Smart Structures and Systems
• /
• v.18 no.3
• /
• pp.389-403
• /
• 2016

Structural deflection can be identified from measured strains from long gague sensors, but the sensor layout scheme greatly influences on the accuracy of identified resutls. To determine the optimal sensor layout scheme for accurate deflection identification of the tied arch bridge, the method of optimal layout of long-gauge fiber optic sensors is studied, in which the characteristic curve is first developed by using the bending macro-strain curve under multiple target load conditions, then optimal sensor layout scheme with different number of sensors are determined. A tied arch bridge is studied as an example to verify the effectiveness and robustness of the proposed method for static and dynamic deflection identification.

• Journal of Microbiology and Biotechnology
• /
• v.27 no.9
• /
• pp.1628-1638
• /
• 2017

Viola tianshanica Maxim, belonging to the Violaceae plant family, is traditionally used in Uighur medicine for treating pneumonia, headache, and fever. There is, however, a lack of basic understanding of its pharmacological activities. This study was designed to observe the effects of the ethanol extract (TSM) from Viola tianshanica Maxim on the inflammation response in acute lung injury (ALI) induced by LPS and the possible underlying mechanisms. We found that TSM (200 and 500 mg/kg) significantly decreased inflammatory cytokine production and the number of inflammatory cells, including macrophages and neutrophils, in bronchoalveolar lavage fluid. TSM also markedly inhibited the lung wet-to-dry ratio and alleviated pathological changes in lung tissues. In vitro, after TSM ($12.5-100{\mu}g/ml$) treatment to RAW 264.7 cells for 1 h, LPS ($1{\mu}g/ml$) was added and the cells were further incubated for 24 h. TSM dose-dependently inhibited the levels of proinflammatory cytokines, such as NO, $PGE_2$, $TNF-{\alpha}$, IL-6, and $IL-1{\beta}$, and remarkably decreased the protein and mRNA expression of $TNF-{\alpha}$ and IL-6 in LPS-stimulated RAW 264.7 cells. TSM also suppressed protein expression of $p-I{\kappa}Ba$ and p-ERK1/2 and blocked nuclear translocation of $NF-{\kappa}B$ p65. The results indicate that TSM exerts anti-inflammatory effects related with inhibition on $NF-{\kappa}B$ and MAPK (p-ERK1/2) signaling pathways. In conclusion, our data demonstrate that TSM might be a potential agent for the treatment of ALI.

• Asia Pacific Journal of Corpus Research
• /
• v.4 no.1
• /
• pp.61-71
• /
• 2023

This study examines the effects of data-driven learning (DDL)-an approach employing corpora for inductive language pattern learning-on error identification in second language (L2) writing. The data consists of error identification instances from fifty-five participants, compared across different reference materials: the Corpus of Contemporary American English (COCA), dictionaries, and no use of reference materials. There are three significant findings. First, the use of COCA effectively identified collocational and form-related errors due to inductive inference drawn from multiple example sentences. Secondly, dictionaries were beneficial for identifying lexical errors, where providing meaning information was helpful. Finally, the participants often employed a strategic approach, identifying many simple errors without reference materials. However, while maximizing error identification, this strategy also led to mislabeling correct expressions as errors. The author has concluded that the strategic selection of reference materials can significantly enhance the effectiveness of error identification in L2 writing. The use of a corpus offers advantages such as easy access to target phrases and frequency information-features especially useful given that most errors were collocational and form-related. The findings suggest that teachers should guide learners to effectively use appropriate reference materials to identify errors based on error types.

• Biotechnology and Bioprocess Engineering:BBE
• /
• v.10 no.3
• /
• pp.248-253
• /
• 2005

AfsR2, originally identified from Streptomyces lividans, is a global regulatory protein which stimulates antibiotic biosynthesis. Through its stable chromosomal integration, the high level of gene expression of afsR2 significantly induced antibiotic production as well as the sporulation of S. lividans, implying the presence of yet-uncharacterized AfsR2-target proteins. To identify and evaluate the putative AfsR2-target proteins involved in antibiotic regulation, the proteomics-driven approach was applied to the wild-type S. lividans and the afsR2-integrated actinorhodin overproducing strain. The 20 gel-electrophoresis gave approximately 340 protein spots showing different protein expression patterns between these two S. lividans strains. Further MALDI-TOF analysis revealed several AfsR2-target proteins, including glyceraldehyde-3-phosphate dehydrogenase, putative phosphate transport system regulator, guanosine penta phosphate synthetase/polyribonucleotide nucleotidyltransferase, and superoxide dismutase, which suggests that the AfsR2 should be a pleiotropic regulatory protein which controls differential expressions of various kinds of genes in Streptomyces species.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
• /
• v.10 no.2
• /
• pp.68-73
• /
• 2011

In Ground Penetrating Radar (GPR) for buried object detection, it is important to identify a buried target because removal of an unwanted target requires as much time and effort as does a wanted target. For a simulation of the target identification, the FDTD (Finite Difference Time Domain) and PML (Perfectly Matched Layer) techniques are widely used. Simulation results vary depending on the type of the buried object and the position of the source. As a result, this paper illustrates the range (time) profile of the five types of facilities including PEC (Perfect Electric Conductor) rectangular box and pipes, and shows the comparison of the range profile of the buried facilities.

• Proceedings of the KSRS Conference
• /
• 2000.04a
• /
• pp.9-9
• /
• 2000

For the planning of future land use for economic activities, an essential component is the identification of the vulnerable areas for natural hazard and environmental impacts from the activities. Also, exploration for mineral and energy resources is carried out by a step by step approach. At each step, a selection of the target area for the next exploration strategy is made based on all the data harnessed from the previous steps. The uncertainty of the selected target area containing undiscovered resources is a critical factor for estimating the exploration risk. We have developed not only spatial prediction models based on adapted artificial intelligence techniques to predict target and vulnerable areas but also validation techniques to estimate the uncertainties associated with the predictions. The prediction models will assist the scientists and decision-makers to make two critical decisions: (i) of the selections of the target or vulnerable areas, and (ii) of estimating the risks associated with the selections.

• Journal of Microbiology and Biotechnology
• /
• v.33 no.1
• /
• pp.83-95
• /
• 2023

These days, bacterial detection methods have some limitations in sensitivity, specificity, and multiple detection. To overcome these, novel detection and identification method is necessary to be developed. Recently, NGS panel method has been suggested to screen, detect, and even identify specific foodborne pathogens in one reaction. In this study, new NGS panel primer sets were developed to target 13 specific virulence factor genes from five types of pathogenic Escherichia coli, Listeria monocytogenes, and Salmonella enterica serovar Typhimurium, respectively. Evaluation of the primer sets using singleplex PCR, crosscheck PCR and multiplex PCR revealed high specificity and selectivity without interference of primers or genomic DNAs. Subsequent NGS panel analysis with six artificially contaminated food samples using those primer sets showed that all target genes were multi-detected in one reaction at 10⁸-10⁵ CFU of target strains. However, a few false-positive results were shown at 10⁶-10⁵ CFU. To validate this NGS panel analysis, three sets of qPCR analyses were independently performed with the same contaminated food samples, showing the similar specificity and selectivity for detection and identification. While this NGS panel still has some issues for detection and identification of specific foodborne pathogens, it has much more advantages, especially multiple detection and identification in one reaction, and it could be improved by further optimized NGS panel primer sets and even by application of a new real-time NGS sequencing technology. Therefore, this study suggests the efficiency and usability of NGS panel for rapid determination of origin strain in various foodborne outbreaks in one reaction.

• Smart Structures and Systems
• /
• v.31 no.4
• /
• pp.421-436
• /
• 2023

This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.