• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• Genomics & Informatics
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• v.14 no.1
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• pp.12-19
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• 2016

Neuropeptides produced from prohormones by selective action of endopeptidases are vital signaling molecules, playing a critical role in a variety of physiological processes, such as addiction, depression, pain, and circadian rhythms. Neuropeptides bind to post-synaptic receptors and elicit cellular effects like classical neurotransmitters. While each neuropeptide could have its own biological function, mass spectrometry (MS) allows for the identification of the precise molecular forms of each peptide without a priori knowledge of the peptide identity and for the quantitation of neuropeptides in different conditions of the samples. MS-based neuropeptidomics approaches have been applied to various animal models and conditions to characterize and quantify novel neuropeptides, as well as known neuropeptides, advancing our understanding of nervous system function over the past decade. Here, we will present an overview of neuropeptides and MS-based neuropeptidomic strategies for the identification and quantitation of neuropeptides.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.41-46
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• 2023

Biometrics is an application of biometric authentication and identification techniques that are used for security. Where people can be identified by physical or behavioral features such as iris, fingerprints, or even voice. Biometrics with cryptography can be used in a variety of applications such as issuing, generating, or associating biometric keys. Biometric identification and cryptography are used in many institutions and high-security systems due to the difficulty of tampering or forgery by hackers. In this paper, literature reviews on biometric identification and cryptography are presented and discussed. In addition to a comparison of techniques in the literature reviews, identifying its strengths and weaknesses, and providing an initial proposal for biometrics and cryptography.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.119-126
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• 2005

Load bearing structural members in a wide variety of applications accumulate damage over their service life. From a standpoint of both safety and performance, it is desirable to monitor the occurrence, location, and extent of such damage. Structures require complicated element models with a number of degrees of freedom in structural analysis. During experiment much effort and cost is needed for measuring structural parameters. The sparseness and errors of measured data have to be considered during the parameter estimation Of Structures. In this paper we introduces damage identification algorithm by a system identification(S.I) using static and dynamic response. To study the behaviour of the estimators in noisy environment Using Monte Carlo simulation and a data measured perturbation scheme is adopted to investigate the influence of measurement errors on identification results. The assessment result by static and dynamic response were compared, and the efficiency and applicabilities of the proposed algorithm are demonstrated through simulated static and dynamic responses of a truss bridge. The assessment results by each method were compared and we could observe that the 5.1 method is superior to the other conventional methods.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.769-774
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• 2016

In the design of sensorless control system for induction motor, high-precision speed estimation is one of the most difficult problems. To solve this problem, the common method is model reference adaptive method (MRAS). MRAS requires accurate motor parameters to estimate rotor speed precisely. However, when motor is running, the variety of temperature and magnetic saturation will lead to the change of motor parameters such as stator resistance and rotor resistance, which will lower the accuracy of the speed estimation. To improve the accuracy and rapidity of speed estimation, this paper analyses the mutual MRAS speed identification based on rotor flux linkage, and proposes an improved mutual MRAS speed identification based on back-EMF. The improved method is verified by Simulink simulation and motor experimental platform based on DSP2812. The results of simulation and experiment indicate that the method proposed by this paper can significantly improve the accuracy of speed identification, and speed up the response of identification.

• Mycobiology
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• v.51 no.4
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• pp.195-209
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• 2023

The seed borne disease such as bakanae is difficult to control. Crop yield loss caused by bakanae depending on the regions and varieties grown, ranging from 3.0% to 95.4%. Bakanae is an important disease of rice worldwide and the pathogen was identified as Fusarium fujikuroi Nirenberg (teleomorph: Gibberella fujikuroi Sawada). Currently, four Fusaria (F. fujikuroi, F. proliferatum, F. verticillioides and F. andiyazi) belonging to F. fujikuroi species complex are generally known as the pathogens of bakanae. The infection occurs through both seed and soil-borne transmission. When infection occurs during the heading stage, rice seeds become contaminated. Molecular detection of pathogens of bakanae is important because identification based on morphological and biological characters could lead to incorrect species designation and time-consuming. Seed disinfection has been studied for a long time in Korea for the management of the bakanae disease of rice. As seed disinfectants have been studied to control bakanae, resistance studies to chemicals have been also conducted. Presently biological control and resistant varieties are not widely used. The detection of this pathogen is critical for seed certification and for preventing field infections. In South Korea, bakanae is designated as a regulated pathogen. To provide highly qualified rice seeds to farms, Korea Seed & Variety Service (KSVS) has been producing and distributing certified rice seeds for producing healthy rice in fields. Therefore, the objective of the study is to summarize the recent progress in molecular identification, fungicide resistance, and the management strategy of bakanae.

• Molecules and Cells
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• v.19 no.3
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• pp.428-435
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• 2005

This study was carried out to assess the potential of SSR markers for variety identification by comparing SSR markers and morphological traits in tests of distinctiveness, uniformity, and stability (DUS) of pepper (Capsicum annuum L.) varieties. Twenty-seven SSR markers were polymorphic in 66 pepper varieties, revealing a total of 89 alleles. Average polymorphism information content (PIC) value was 0.529, ranging from 0.03 to 0.877. Cluster analysis of the band patterns separated the varieties into three groups corresponding to varietal types. Morphological trait-based clustering showed some degree of similarity to dendrogram topologies based on the SSR index. However, no significance correlation was found between the SSR and morphological data. SSR markers could be used to complement a DUS test of a candidate variety and to select complimentary varieties by pre-screening existing varieties in the context of protecting new varieties of pepper.

• Archives of Pharmacal Research
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• v.13 no.1
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• pp.105-107
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• 1990

The absence, in the biomass, of glutamic-oxalacetic and glutamic-pyruvic transaminases and the prevalance of gamma-glutamic transpeptidase were taken as basic criteria to differentiate between Erwinia carotovora var. carorovora from E. carotovora var, citrullis and E. toxica. For further identification, detection of cholesterol in the biomass confirmed the toxica species whereas the absence of glucose confirmed the citrullis variety.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.709-712
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• 2003

Recently, high noise problem was experienced during the development of 2-pole squirrel cage motor for industrial compressor. In order to firstly identify the noise characteristics, a variety of measurements were carried out. It was found out that high noise was dominated by linear and nonlinear slot noise components. For the development of low noise indusrial motor, the air gap between rotor and stator in the motor was firstly enlarged. Secondly, it was also modified for the cooling housing to have high absorption features. Consequencely, low noise 2-pole motor having the noise level of less 80㏈(A) was developed. In this paper, a series of noise identification and control process for this motor are introduced.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.10
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• pp.367-375
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• 1983

An extended Kalman filter (EKF) algorithm for estimating aerodynamic parameters from missile flight data is evaluated using simulated test data. The algorithm includes a general purpose 6-DOF missile airframe suitable for representing a variety of missile configurations. The EKF is demonstrated to be well suited as a postflight analysis tool for extracting large numbers of airframe parameters from flight test measurements. A structure identification algorithm is evaluated using synthetic measurement data. This algorithm used in conjunction with the parameter identification algorithm, can select that model from a family of candidate models which most likely produced the synthetic measurement data.