• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.185-204
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• 2011

Fast Fashion (fast fashion) is to reflect the latest trends and quickly create an immediate and quick with words related to clothing to distribute immediately reflect the latest fashion design, a relatively low cost, rapid product turnover means to succeed in fashion or business. The popularity of fast fashion is growing in the recent domestic fashion market. In this study, fast-fashion consumers' purchasing behavior recognition for brand identification and brand personality, brand reputation and brand identification, brand attitude, and affect the relationship between customer loyalty will be discussed. The results of this study can be summarized as follows. First, In this study, based on existing studies, brand personality and brand identification through a process that affects customer loyalty reaffirmed. Second, the 5 dimensions of brand personality and brand identification of the factors found by the sophistication and unique. Third, the brand's reputation in the brand identification had a significant impact. Fourth, brand identification, brand attitude and the impact on customer loyalty was significant.

• The Research Journal of the Costume Culture
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• v.28 no.2
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• pp.147-165
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• 2020

To identify the antecedents of repurchasing intention toward fast fashion brands, this study was conducted to examine brand authenticity and brand identification as both direct and indirect antecedents of repurchasing intention through fast fashion brand love. Through convenience sampling, 266 university students in Seoul metropolitan area completed a questionnaire survey. Data were analyzed using SPSS for exploratory factor analysis, and AMOS was used for confirmatory factor analysis and path analysis. Factor analysis revealed the following: for brand authenticity, four dimensions('originality,' 'reliability,' 'continuity,' and 'naturalness') were revealed; for both consumer brand identification and repurchase intention one dimension was revealed; and for brand love two dimensions were revealed('passion' and 'affection'). Path analysis confirmed that 'reliability' and 'naturalness'in relation to brand authenticity indirectly influenced repurchase intention through 'passion'(as a factor of brand love) and directly influenced repurchase intention. Further, 'continuity' in relation to brand authenticity indirectly influenced repurchase intention through 'affection'(as a factor of brand love) and directly influenced repurchase intention. Consumer brand identification influenced repurchase intention indirectly through two factors of brand love. These results suggest that fast fashion brand marketers should implement effective strategies that consider consumers'perceptions of brand authenticity, consumer brand identification, and brand love.

• YAKHAK HOEJI
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• v.35 no.1
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• pp.1-6
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• 1991

Fast Hartley transform(FHT) was used for the identification of derivative UV spectra of pharmaceuticals, with the advantages of relatively shorter computing time of FHT and more precise results. The arccosine value of dot product of two vectors of normalized FHT coefficients calculated from two compared derivative spectra was a reasonable parameter for the spectral identification. Using this parameter, the similar patterns of derivative spectra of 13 penicillins can be differenciated from each other. The concentration difference and the minor contamination did not interfere the results of identification procedures. All these procedures of identification were accomplished successfully by the computer program, [SPECMAN PLUS] version 1.30, which was developed for this article.

• Journal of The Korean Astronomical Society
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• v.34 no.1
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• pp.1-8
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• 2001

We present a fast reduction method of survey data obtained using a single-dish radio telescope. Along with a brief review of classical method, a new method of identification and elimination of negative and positive bad channels are introduced using cloud identification code and several IRAF (Image Reduction and Analysis Facility) tasks relating statistics. Removing of several ripple patterns using Fourier Transform is also discussed. It is found that BACKGROUND task within IRAF is very efficient for fitting and subtraction of base-line with varying functions. Cloud identification method along with the possibility of its application for analysis of cloud structure is described, and future data reduction method is discussed.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.1024-1031
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• 2019

The Molten Salt Fast Reactor (MSFR) with its liquid circulating fuel and its fast neutron spectrum calls for a new safety approach including technological neutral methodologies and analysis tools adapted to early design phases. In the frame of the Horizon2020 program SAMOFAR (Safety Assessment of the Molten Salt Fast Reactor) a safety approach suitable for Molten Salt Reactors is being developed and applied to the MSFR. After a description of the MSFR reference design, this paper focuses on the identification of the Postulated Initiating Events (PIEs), which is a core part of the global assessment methodology. To fulfil this task, the Functional Failure Mode and Effect Analysis (FFMEA) and the Master Logic Diagram (MLD) are selected and employed separately in order to be as exhaustive as possible in the identification of the initiating events of the system. Finally, an extract of the list of PIEs, selected as the most representative events resulting from the implementation of both methods, is presented to illustrate the methodology and some of the outcomes of the methods are compared in order to highlight symbioses and differences between the MLD and the FFMEA.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.8
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• pp.39-48
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• 1997

The fast redundancy identification is required to perform an efficient test pattern genration. Due to the reconvergent fanouts which make the dependency among objectives and the fault propagation blocking, there may exist redundnat faults in the cirucit. This paper presents the isomorphism identification and the pseudo dominator algorithms which are useful to identify redundant faults in combinational circuits. The isomorphism identification algorithm determines whether mandatory objectives required for fault detection cannot be simultaneously satisfied from primary input assignments or not using binary decision diagrma. The pseudo dominator algorithm determines whether faults propagation is possible or not by considering all paths at a given fanout node. Several experiments using ISCAS 85 benchmark circuits demonstrate the efficiency and practicability of the algorithms.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.561-563
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• 1997

In this paper, we identified the Black-box system with serious nonlinerity and fast dynamics using Neural Network. This NN have new structure and learned by RLS. It identify system in real-time without priori data. We use this NN to 7-DOF vehicle identification.

• Smart Structures and Systems
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• v.8 no.4
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• pp.367-384
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• 2011

This paper presents the design and experimental evaluation of fast output sampling feedback controller to minimize structural vibration of a cantilever beam using Shape Memory Alloy (SMA) wires as control actuators and piezoceramics as sensor and disturbance actuator. Linear dynamic models of the smart cantilever beam are obtained using online recursive least square parameter estimation. A digital control system that consists of $Simulink^{TM}$ modeling software and dSPACE DS1104 controller board is used for identification and control. The effectiveness of the controller is shown through simulation and experimentation by exciting the structure at resonance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6B
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• pp.450-455
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• 2008

We analyze the tag identification procedure of conventional EPC Class 1 RFID system and propose the fast anti-collision algorithm for the performance improvement of the system. In the proposed algorithm, the reader uses information of tag collisions and reduces unnecessary procedures of the conventional algorithm. We evaluate the performance of the proposed anti-collision algorithm and the conventional algorithm using mathematical analysis and simulation. According to the results, the fast anti-collision algorithm shows greatly better performance than conventional algorithm.

• Journal of the Korean Wood Science and Technology
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• v.45 no.6
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• pp.797-808
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• 2017

Automatic wood species identification systems have enabled fast and accurate identification of wood species outside of specialized laboratories with well-trained experts on wood species identification. Conventional automatic wood species identification systems consist of two major parts: a feature extractor and a classifier. Feature extractors require hand-engineering to obtain optimal features to quantify the content of an image. A Convolutional Neural Network (CNN), which is one of the Deep Learning methods, trained for wood species can extract intrinsic feature representations and classify them correctly. It usually outperforms classifiers built on top of extracted features with a hand-tuning process. We developed an automatic wood species identification system utilizing CNN models such as LeNet, MiniVGGNet, and their variants. A smartphone camera was used for obtaining macroscopic images of rough sawn surfaces from cross sections of woods. Five Korean softwood species (cedar, cypress, Korean pine, Korean red pine, and larch) were under classification by the CNN models. The highest and most stable CNN model was LeNet3 that is two additional layers added to the original LeNet architecture. The accuracy of species identification by LeNet3 architecture for the five Korean softwood species was 99.3%. The result showed the automatic wood species identification system is sufficiently fast and accurate as well as small to be deployed to a mobile device such as a smartphone.