• Smart Structures and Systems
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• v.5 no.4
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• pp.469-482
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• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.448-451
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• 2002

This study will offer multi-feature recognition instead of an using mono-feature to improve the accuracy of recognition. Each Feature can be found by following ways. For a face, the feature is calculated by the principal component analysis with wavelet multiresolution. For a lip, a filter is used to find out on equation to calculate the edges of the lips first. Then the other feature is calculated by the distance ratio of facial parameters. We've sorted backpropagation neural network and experimented with the inputs used above and then based on the experimental results we discuss the advantage and efficiency.

• Korean Journal of Ichthyology
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• v.25 no.4
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• pp.234-238
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• 2013

Based on a single juvenile specimen (32.3 mm SL) collected from the northeastern coastal waters of Goseong, Gangwon-do, Nautichthys pribilovius was described as the first juvenile record from Korea. This juvenile fish is characterized by having entire body covered with close-set villous prickles, a blunt triangular ridge above orbit with a palmate cirrus, two blunt occipital projections, preopercle with four blunt spines, and a blackish bar below eye reaching lower margin of preopercle. Some morphometric characters related with growth were also discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.422-425
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• 2009

RFID (Radio Frequency IDentificaiton)는 태그, 레이블, 카드 등에 저장된 데이터를 무선 주파수를 이용하여 리더에서 자동 인식하는 기술이다. RFID 애플리케이션은 RFID 태그의 실시간 정보를 기반으로 하는 업무 프로세스를 의미하는 것으로, RFID 정보를 이용하기 위해서는 기존의 비즈니스 프로세스가 변형되어져야 한다. RFID 미들웨어로부터 발생하는 저수준의 RFID 이벤트를 다양한 정보 서버들을 참조하여 고수준의 이벤트로 변환시키기 위한 일련의 활동(activity)들을 대부분의 RFID 애플리케이션에서 공통으로 수행하기 때문에 이러한 활동들을 재사용 될 수 있는 핵심자산으로 만들어놓을 필요가 있다. 본 논문에서는 다양한 유형의 RFID 애플리케이션에 재사용될 수 있는 RFID 관련 활동들을 RFID 제네릭 (generic) 활동으로 구분하고 이를 이용하여 2-레벨의 비즈니스 프로세스 패밀리 모델 (Business Process Family Model: BPFM)을 구축하는 방법을 제시한다. 상위 레벨의 RFID 제네릭 액티비티들은 두번에 걸쳐 가변치가 결정될 수 있는 가변점을 가지게 된다. 하위 레벨을 구성하는 도메인 활동들은 그 자체의 가변속성 뿐만 아니라 활동의 흐름에서 나타나는 다양한 형태의 가변요소들을 표현하게 된다. 이러한 2-레벨 BPFM을 이용함으로써 RFID 시스템 도입 시 처리해야 하는 활동들의 개발 양을 현저히 줄일 수 있다.

• BMB Reports
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• v.35 no.4
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• pp.403-408
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• 2002

A hypothetical 21.0 kDa protein (ORF O197) from Escherichia coli K-12 was cloned, purified, and characterized. The protein sequence of ORF O197(termed EcO197) shares a 33.5% identity with that of a novel NTPase from Methanococcus jannaschii. The EcO197 protein was purified using Ni-NTA affinity chromatography, protease digestion, and gel filtration column. It hydrolyzed nucleoside triphosphates with an O6 atom-containing purine base to nucleoside monophosphate and pyrophosphate. The EcO197 protein had a strong preference for deoxyinosine triphosphate (dITP) and xanthosine triphosphate (XTP), while it had little activity in the standard nucleoside triphosphates (dATP, dCTP, dGTP, and dTTP). These aberrant nucleotides can be produced by oxidative deamination from purine nucleotides in cells; they are potentially mutagenic. The mutation protection mechanisms are caused by the incorporation into DNA of unwelcome nucleotides that are formed spontaneously. The EcO197 protein may function to eliminate specifically damaged purine nucleotide that contains the 6-keto group. This protein appears to be the first eubacterial dITP-and XTP-hydrolyzing enzyme that has been identified.

• Natural Product Sciences
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• v.20 no.2
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• pp.126-129
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• 2014

Bioactivity-guided investigation on whole plant of Euphorbia supina, using LPS-induced Raw264.7 cells, led to the identificaiton of a tannin which was not reported from this plant along with four known constituents (quercetin, astragalin, juglanin and methyl gallate). The structure of the tannin was determined as corilagin by the interpretation of NMR (1D and 2D) and MS spectroscopic data. All the isolates were tested for the inhibitory activity against NO production in LPS-induced Raw264.7 cells. Among the tested isolates, corilagin was found to be the most active compound.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.10a
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• pp.180-181
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.

• The Journal of the Acoustical Society of Korea
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• v.16 no.6
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• pp.25-35
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• 1997

Most of speech analysis methods developed up to date are based on second order statistics, and one of the biggest drawback of these methods is that they show dramatical performance degradation in noisy environments. On the contrary, the methods using higher order statistics(HOS), which has the property of suppressing Gaussian noise, enable robust feature extraction in noisy environments. In this paper we propose a text-independent speaker identification system using higher order statistics and compare its performance with that using the conventional second-order-statistics-based method in both white and colored noise environments. The proposed speaker identification system is based on the vector quantization approach, and employs HOS-based voiced/unvoiced detector in order to extract feature parameters for voiced speech only, which has non-Gaussian distribution and is known to contain most of speaker-specific characteristics. Experimental results using 50 speaker's database show that higher-order-statistics-based method gives a better identificaiton performance than the conventional second-order-statistics-based method in noisy environments.

• Journal of Navigation and Port Research
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• v.34 no.10
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• pp.727-733
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.

• Korean Journal of Environmental Agriculture
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• v.13 no.2
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• pp.199-208
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• 1994

Analytical methods for the determination of the derivatives of the herbicide (${\pm}$)-2-(4-chloro-2-methylphenoxy)propionic acid (MCPP) by capillary column gas chromatography with mass spectrometer (GC-MS) and electron-capture detection (GC-ECD) were studied. A successful procedure was introduced for the ester preparation using $H_2SO_4$, as the catalyst and the alcohol 2,2,2-trichloroethanol (TCE) or 2,2,2-trifluoroethanol (TFE). The identificaiton and elucidation of MCPP by GC-MS spectrometry following the esterification with diazomethane, $BF_3$/methanol, $H_2SO_4$/methanol, TCE, TFE, or pentafluorobenzyl bromide (PFB) were carried out. A comparison of the response-sensitivities among those MCPP esters was made with GC-ECD. Although the methylation product of MCPP was confirmed by GC-MS, its low sensitivity to the ECD limited the detection of MCPP. TCE, TFE, and PFB derivatization methods resulted in a high rate of MCPP esterifications and very sensitive ECD molecular responses. Based on efficiency, convenience, worker safety, and least sample contamination, TFE esterificaiton was considered as the superior method for MCPP analysis to the other methods of derivatization. An accurate method is described for quantifying MCPP in soil leachates by GC-ECD at very low concentrations without the requirement of a complicated clean-up process. As a result, MCPP residues at concentrations of less than $0.1{\mu}g$ in 100ml soil leachate were detected.