• Food Science of Animal Resources
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• v.21 no.3
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• pp.246-255
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• 2001

Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) of muscles extracted with distilled water, saline solution, SDS or Trition X-100 showed simular protein patterns between Hanwoo and Holstein meat, indicating that SDS-PAGE technique may not be useful for the identification between Hanwoo and Holstein meat. Lectine blot analysis of muscle extracted with distilled water demonstrated that Hanwoo and Holstein meat had similar affinities for concanavalin A (Con A), ricinus communis agglutinin (RCA-120), ulex europaeus agglutinin (UEA-1) or peanut agglutinin (PNA) lectins. However, approximately 32.1 kDa component of Hanwoo meat showed high affinity for dolichos biflorus agglutinin (DBA) lectin. On the contrary, high molecular weight components of Holstein meat had the specific affinity for wheat germ agglutinin (WGA) lectin. Hanwoo meat-specific components were observed by lectin staining of heat-denatured meat at 100$^{\circ}C$ for 30 sec. Also, the component of heat-denatured meat at 100$^{\circ}C$ for 30 sec, which was slightly smaller than Hanwoo meat-specific component, was concentrated specifically in Holstein meat.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.789-797
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• 2017

Recently, some integrated structural identification/damage detection and reliability evaluation of structures with uncertainties have been proposed. However, these techniques are applicable for off-line synthesis of structural identification and reliability evaluation. In this paper, based on the recursive formulation of the extended Kalman filter, an on-line integration of structural identification/damage detection and reliability evaluation of stochastic building structures is investigated. Structural limit state is expanded by the Taylor series in terms of uncertain variables to obtain the probability density function (PDF). Both structural component reliability with only one limit state function and system reliability with multi-limit state functions are studied. Then, it is extended to adopt the recent extended Kalman filter with unknown input (EKF-UI) proposed by the authors for on-line integration of structural identification/damage detection and structural reliability evaluation of stochastic building structures subject to unknown excitations. Numerical examples are used to demonstrate the proposed method. The evaluated results of structural component reliability and structural system reliability are compared with those by the Monte Carlo simulation to validate the performances of the proposed method.

• Smart Structures and Systems
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• v.11 no.6
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• pp.589-604
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• 2013

Identification of damage has become an evolving area of research over the last few decades with increasing the need of online health monitoring of the large structures. The visual damage detection can be impractical, expensive and ineffective in case of large structures, e.g., offshore platforms, offshore pipelines, multi-storied buildings and bridges. Damage in a system causes a change in the dynamic properties of the system. The structural damage is typically a local phenomenon, which tends to be captured by higher frequency signals. Most of vibration-based damage detection methods require modal properties that are obtained from measured signals through the system identification techniques. However, the modal properties such as natural frequencies and mode shapes are not such good sensitive indication of structural damage. Identification of damaged jacket type offshore platform members, based on wavelet packet transform is presented in this paper. The jacket platform is excited by simple wave load. Response of actual jacket needs to be measured. Dynamic signals are measured by finite element analysis result. It is assumed that this is actual response of the platform measured in the field. The dynamic signals first decomposed into wavelet packet components. Then eliminating some of the component signals (eliminate approximation component of wavelet packet decomposition), component energies of remained signal (detail components) are calculated and used for damage assessment. This method is called Detail Signal Energy Rate Index (DSERI). The results show that reduced wavelet packet component energies are good candidate indices which are sensitive to structural damage. These component energies can be used for damage assessment including identifying damage occurrence and are applicable for finding damages' location.

• Smart Structures and Systems
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• v.6 no.1
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• pp.39-56
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• 2010

Structural Control relies, with a great deal, on the ability of the control algorithm to identify the current state of the system, at any given point in time. When such algorithms are designed to perform in a smart manner, several smart technologies/devices are called upon to perform tasks that involve pattern recognition and control. Smart pattern recognition is proposed to replace/enhance traditional state identification techniques, which require the extensive manipulation of intricate mathematical equations. Smart pattern recognition techniques attempt to emulate the behavior of the human brain when performing abstract pattern identification. Since these techniques are largely heuristic in nature, it is reasonable to ensure their reliability under real life situations. In this paper, a neural network pattern recognition scheme is explored. The pattern identification of three structural systems is considered. The first is a single bay three-story frame. Both the second and the third models are variations on benchmark problems, previously published for control strategy evaluation purposes. A Neural Network was developed and trained to identify the deformed shape of structural systems under earthquake excitation. The network was trained, for each individual model system, then tested under the effect of a different set of earthquake records. The proposed smart pattern identification scheme is considered an integral component of a Smart Structural System. The Reliability assessment of such component represents an important stage in the evaluation of an overall reliability measure of Smart Structural Systems. Several studies are currently underway aiming at the identification of a reliability measure for such smart pattern recognition technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3779-3784
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• 2012

Real-time process monitoring and diagnosis of industrial processes is one of important operational tasks for quality and safety reasons. The objective of fault diagnosis or identification is to find process variables responsible for causing a specific fault in the process. This helps process operators to investigate root causes more effectively. This work assesses the applicability of combining a nonlinear statistical technique of kernel Fisher discriminant analysis with a preprocessing method as a tool of on-line fault identification. To compare its performance to existing linear principal component analysis (PCA) identification scheme, a case study on a benchmark process was performed to show that the fault identification scheme produced more reliable diagnosis results than linear method.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.268-280
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• 2023

Several companies have migrated their existing monolithic web applications to microservice architectures. Consequently, research on the identification of microservices from monolithic web applications has been conducted. Meanwhile, the use-case model plays a crucial role in outlining the system's functionalities at a high level of abstraction, and studies have been conducted to identify microservices by utilizing this model. However, previous studies on microservice identification utilizing use-cases did not consider the components executed in the presentation layer. Unlike existing approaches, this paper proposes a technique that considers all three layers of web applications (presentation, business logic, and data access layers). Initially, the components used in the three layers of a web application are extracted by executing all the scenarios that constitute its use-cases. Thereafter, the usage rate of each component is determined for each use-case and the component is allocated to the use-case with the highest rate. Then, each use-case is realized as a microservice. To verify the proposed approach, microservice identification is performed using open-source web applications.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.583-592
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• 2000

This paper proposes feature parameter transformation method using independent component analysis (ICA) for speaker identification. The proposed method assumes that the cepstral vectors from various channel-conditioned speech are constructed by a linear combination of some characteristic functions with random channel noise added, and transforms them into new vectors using ICA. The resultant vector space can give emphasis to the repetitive speaker information and suppress the random channel distortions. Experimental results show that the transformation method is effective for the improvement of speaker identification system.

• Journal of KSNVE
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• v.4 no.3
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• pp.327-335
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• 1994

In this paper, to identify the dynamic characteristics of antenna system, the antenna is divided into 4 components and those were analyzed with a conventional FEM package MSC/NASTRAN. Using a Component Mode Synthesis Method, dynamic characteristics of total system is also identified. The Coherence of each component to total system is evaluated by using strain and kinetic component to total system is evaluated by using strain and kinetic energy. The improving strategy of dynamic characteristics is suggested by changing mass and stiffness of large coherence components.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.3
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• pp.35-43
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• 2012

Medium size rotorcraft consist of approximately 5,000 key components. The components must satisfy the target weight and performance requirement through optimization. Therefore a rotorcraft component has approximately 100 times higher unit cost for mass production than the equivalent of an automobile's, along with huge development cost. Configuration management consists of four main parts : configuration identification, configuration control, configuration audit, and data management. In development programme, configuration management is one of the methods to save development cost, and setting a well-structured configuration management system according to the Military Standard is an important factor in success of the programme. The paper proposes a configuration management system suitable for development of various multi-use components development and presents that the configuration management was performed successfully during dual-use component development programme using the established system.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.1
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• pp.48-54
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• 2011

As personal or compact devices with image acquisition functionality are becoming easily available for common users, the voluminous images that need to be managed by image related services or systems demand efficient and effective methods in the perspective of image identification. The objective of image identification is to associate an image with a unique identifier. Moreover, whenever an image identifier needs to be regenerated, the newly generated identifier should be consistent. In this paper, we propose three image identifier generation methods utilizing image features: linear component, luminance area, and combination of both features. The linear component based method exploits the information of distribution of partial lines over an image, while the luminance area based method utilizes the partition of an image into a number of small areas according to the same luminance degree. The third method is proposed in order to take advantage of both former methods. In this paper, we also demonstrate the experimental evaluations for uniqueness and similarity analysis that have shown favorable results.