• Title/Summary/Keyword: identification process

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A Reform Measure of the Structure and Transaction Process for the Safety Improvement of a Credit Card (신용카드의 안전성 향상을 위한 구조 및 거래절차 개선방법)

  • Lee, Young Gyo;Ahn, Jeong Hee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.7 no.3
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    • pp.63-74
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    • 2011
  • Credit cards are more convenient than cash of heavy. Therefore, credit cards are used widely in on_line (internet) and off_line in nowadays. To use credit cards on internet is commonly secure because client identification based security card and authentication certificate. However, to use in off_line as like shop, store, department, restaurant is unsecure because of irregular accident. As client identification is not used in off_line use of credit cards, the irregular use of counterfeit, stolen and lost card have been increasing in number recently. Therefore, client identification is urgently necessary for secure card using in off_line. And the method of client identification must be simple, don't take long time, convenient for client, card affiliate and card company. In this paper, we study a reform measure of the structure and transaction process for the safety improvement of a credit cards. And we propose several authentication method of short-and long-term for client identification. In the proposal, the client authentication method by OTP application of smart-phone is efficient nowadays.

A Practical Method for Identification of Nonlinear Chemical Processes by use of Volterra Kernel Model

  • Numata, Motoki;Kashiwagi, Hiroshi;Harada, Hiroshi
    • 제어로봇시스템학회:학술대회논문집
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    • 1999.10a
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    • pp.145-148
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    • 1999
  • It is known that Volterra kernel models can represent a wide variety of nonlinear chemical processes. Also, it is necessary for Volterra model identification to excite the process to be identified with a signal having wide range of frequency spectrum and high enough amplitude of input signals. Kashiwagi[4 ∼ 7] has recently shown a method for measuring Volterra kernels up to third order using pseudorandom M-sequence signals. However, in practice, since it is not always possible to apply such input sequences to the actual chemical plants. Even when we can apply such a pseudorandom signal to the process, it takes much time to obtain higher order Volterra kernels. Considering these problems, the authors propose here a new method for practical identification of Volterra kernels by use of approximate open differential equation (ODE) model and simple plant test. Simulation results are shown for verifying the usefulness of our method of identification of nonlinear chemical processes.

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Efficient Class Identification based on Event (이벤트 기반의 효율적인 클래스 식별)

  • Choi, Mi-Sook;Lee, Jong-Suk
    • Journal of Digital Contents Society
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    • v.9 no.2
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    • pp.165-175
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    • 2008
  • Currently, software development methods have been advanced to service-oriented from component-oriented, to component-oriented from object-oriented. The component-oriented and service-oriented software development methods are analyzed by object-oriented UML model. So, the efficient analysis method for object-oriented UML model needs. In this paper, we suggest the analysis guideline and process based on event using Input Data-Process-Output Data Table for identifying use cases and classes efficiently. And the suggested method complements the problems depending the developer's perspective and experience.

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A study on the adaptive predictive control of steam-reforming plant using bilinear model (쌍일차 모델을 이용한 스팀개질 플랜트의 적응예측제어에 관한 연구)

  • 오세천;여영구
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.156-159
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    • 1996
  • An adaptive predictive control for steam-reforming plant which consist of a steam-gas reformer and a waste heat steam-boiler was studied by using MIMO bilinear model. The simulation experiments of the process identification were performed by using linear and bilinear models. From the simulation results it was found that the bilinear model represented the dynamic behavior of a steam-reforming plant very well. ARMA model was used in the process identification and the adaptive predictive control. To verify the performance and effectiveness of the adaptive predictive controller proposed in this study the simulation results of steam-reforming plant control based on bilinear model were compared to those of linear model. The simulation results showed that the adaptive predictive controller based on bilinear model provides better performance than those of linear model.

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On order determination in identification of closed-loop systems

  • Oura, Kunihiko;Akizuki, Kageo;Hanazaki, Izumi
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.480-483
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    • 1995
  • Identification of a process in closed-loop control system is an important problem in practice. This paper deals with parameter estimation using input-output data of the process operating in a closed-loop system. It is necessary to determine orders and delay-time to get consistent estimators by least square method for input-output data collected from the process. The authors considered a problem to determine delay-time in the condition that orders were known, in last KACC. So we extend the range to determine orders and delay-time in this paper.

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A Study on Initiating Events Identification of the IS Process

  • Cho, Nam-Chul;Jae, Moo-Sung;Eon, Yang-Joon
    • International Journal of Safety
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    • v.5 no.1
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    • pp.29-32
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    • 2006
  • There has been an increasing need for substitute energy development due to the dry up of the fossil fuel and environmental problems. Among the substitute energy under consideration, producing hydrogen from water without the accompanying release of carbon has become a promising technology. Also, Iodine-Sulfur (IS) thermochemical water decomposition is one of the promising processes that can produce hydrogen efficiently using the high temperature gas-cooled reactor (HTGR) as an energy source capable of supplying heat at over 1000. In this study, to effect an initiating events identification of the IS process, Master Logic Diagram (MLD) was used and 9 initiating events that cause a leakage of the chemical material were identified.

Modeling and Identification of Paper Plants based on PRS (PRS를 이용한 제지공정의 인식 및 모델링에 관한 연구)

  • 오창훈;여영구;강홍
    • Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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    • 2004.11a
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    • pp.221-232
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    • 2004
  • Paper process is complex and multivariable system. Identification of a paper process model is imperative for the development of predictive control method. 13-level Pseudo-Random Sequence Signals were used to identify the plant model in which the neural network model was considered model as a real paper process. Results of simulations for identification using 13-level PRS signals and Prediction Error Method are compared with plant operation data. From the comparison, we can see that the dynamics of the model show good agreement with those of real plant.

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Optimization of Automated Suspension Trapping Digestion in Bottom-Up Proteomics via Mass Spectrometry

  • Haneul Song;Yejin Jeon;Iyun Choi;Minjoong Joo;Jong-Moon Park;Hookeun Lee
    • Mass Spectrometry Letters
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    • v.15 no.1
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    • pp.62-68
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    • 2024
  • The Suspension Trapping (S-Trap) method has been a prominent sample preparation technique since its introduction in 2014. Its capacity to induce protein aggregation using organic solvents has significantly improved protein purification and facilitated peptide identification. However, its full potential for automation has been limited by the lack of a suitable liquid handling system until recently. In this study, we aimed to enhance the automation of S-Trap sample preparation by optimizing the S-Trap digestion process, incorporating triethylammonium bicarbonate (TEAB) and CaCl2. The utilization of TEAB buffer conditions in this innovative process led to a noteworthy 12% improvement in protein identification. Additionally, through careful observation of various incubation conditions, we streamlined the entire sample preparation workflow into a concise 4 hours timeline, covering reduction, alkylation, and trypsin incubation stages. This refined and expedited automated S-Trap digestion process not only showcased exceptional time efficiency but also improved trypsin digestion, resulting in increased protein identification.

A study of the influence of Brand Personality and Brand Identification on Customers' Loyalty focusing on the Fast-Fashion (패스트패션의 브랜드 개성과 브랜드 동일시가 고객충성도에 미치는 영향에 관한 연구)

  • Kim, Yong-Bum;Bang, Dong-Won
    • 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.

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A Study on the System Identification based on Neural Network for Modeling of 5.1. Engines (S.I. 엔진 모델링을 위한 신경회로망 기반의 시스템 식별에 관한 연구)

  • 윤마루;박승범;선우명호;이승종
    • Transactions of the Korean Society of Automotive Engineers
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    • v.10 no.5
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    • pp.29-34
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    • 2002
  • This study presents the process of the continuous-time system identification for unknown nonlinear systems. The Radial Basis Function(RBF) error filtering identification model is introduced at first. This identification scheme includes RBF network to approximate unknown function of nonlinear system which is structured by affine form. The neural network is trained by the adaptive law based on Lyapunov synthesis method. The identification scheme is applied to engine and the performance of RBF error filtering Identification model is verified by the simulation with a three-state engine model. The simulation results have revealed that the values of the estimated function show favorable agreement with the real values of the engine model. The introduced identification scheme can be effectively applied to model-based nonlinear control.