• Title/Summary/Keyword: Identification

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Fuzzy Relation-Based Fuzzy Neural-Networks Using a Hybrid Identification Algorithm

  • Park, Ho-Seung;Oh, Sung-Kwun
    • International Journal of Control, Automation, and Systems
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    • v.1 no.3
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    • pp.289-300
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    • 2003
  • In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.

Target identification for visual tracking

  • Lee, Joon-Woong;Yun, Joo-Seop;Kweon, In-So
    • 제어로봇시스템학회:학술대회논문집
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    • pp.145-148
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    • 1996
  • In moving object tracking based on the visual sensory feedback, a prerequisite is to determine which feature or which object is to be tracked and then the feature or the object identification precedes the tracking. In this paper, we focus on the object identification not image feature identification. The target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrica relationship between model segments and extracted line segments. We demonstrate the robustness and feasibility of the proposed target identification algorithm by a moving vehicle identification and tracking in the video traffic surveillance system over images of a road scene.

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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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    • 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.

Automatic Identification of Business Services Using EA Ontology (EA 온톨로지 기반 비즈니스 서비스 자동 식별방안)

  • Jeong, Chan-Ki;Hwang, Sang-Kyu
    • Journal of Information Technology Services
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    • v.9 no.3
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    • pp.179-191
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    • 2010
  • Service identification and composition is one of the key characteristics for a successful Service-Oriented Computing, being receiving a lot of attention from researchers in recent years. In the Service-Oriented Analysis, the identification of business services has to be preceded before application services are identified. Most approaches addressing the derivation of business services are based on heuristic methods and human experts. The manual identification of business services is highly expensive and ambiguous task, and it may result in the service design with bad quality because of errors and misconception. Although a few of approaches of automatic service identification are proposed, most of them are in focus on technical architectures and application services. In this paper, we propose a model on the automatic identification of business services by horizontal and vertical service alignment using Enterprise Architecture as an ontology. We verify the effectiveness of the proposed model of business services identification through a case study based on Department of Defense Enterprise Architecture.

On-line System Identification using State Observer

  • Park, Duck-Gee;Hong, Suk-Kyo
    • 제어로봇시스템학회:학술대회논문집
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    • pp.2538-2541
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    • 2005
  • This paper deals one of the methods of system identification, especially on-line system identification in time-domain. The algorithm in this study needs all states of the system as well input to it for system identification. In this reason, Kalman filter is used for state estimation. But in order to implement a state estimator, the fact that a system model must be known is logical contradiction. To overcome this, state estimation and system parameter estimation are performed simultaneously in one sample. And the result of the system parameter estimation is used as basis to state estimation in next sample. On-line system identification comes, in every sample by performing both processes of state estimation and parameter estimation that are related mutually and recursively. This paper demonstrates the validity of proposed algorithm through an example of an unstable inverted pendulum system. This algorithm can be useful for on-line system identification of a system that has fewer number of measurable output than system order or number of states.

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A Method for Protein Identification Based on MS/MS using Probabilistic Graphical Models (확률그래프모델을 이용한 MS/MS 기반 단백질 동정 기법)

  • Li, Hong-Lan;Hwang, Kyu-Baek
    • Proceedings of the Korean Information Science Society Conference
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    • pp.426-428
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    • 2012
  • In order to identify proteins that are present in biological samples, these samples are separated and analyzed under the sequential procedure as follows: protein purification and digestion, peptide fragmentation by tandem mass spectrometry (MS/MS) which breaks peptides into fragments, peptide identification, and protein identification. One of the widely used methods for protein identification is based on probabilistic approaches such as ProteinProphet and BaysPro. However, they do not consider the difference in peptide identification probabilities according to their length. Here, we propose a probabilistic graphical model-based approach to protein identification from MS/MS data considering peptide identification probabilities, number of sibling peptides, and peptide length. We compared our approach with ProteinProphet using a yeast MS/MS dataset. As a result, our model identified 27 more proteins than ProteinProphet at 1% of FDR (false discovery rate), confirming the importance of peptide length information in protein identification.

The Impacts of Employee-Perceived Brand Personality on Employee Brand Identification : Focused on Food & Beverage Department of Deluxe Hotels in Seoul (브랜드 개성과 종사원 개성이 종사원 브랜드 동일시에 미치는 영향 : 서울 소재 특 1급 호텔 식음료.조리 부서를 중심으로)

  • Choi Mi-Kyung
    • Journal of the East Asian Society of Dietary Life
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    • v.16 no.2
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    • pp.207-214
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    • 2006
  • The purpose of this study was to examine the impacts of brand personality and employee personality on employee brand identification. The questionnaire developed for this study was distributed to 460 employees in F&B (food and beverage) departments and kitchen of 11 deluxe hotels in Seoul. A total of 398 questionnaires were used for analysis (86.5%) and the statistical analyses were completed using SPSS Win(12.0) for descriptive analysis, reliability analysis, t-test, and regression analysis. The results showed that employee brand identification was stronger at higher position, and also stronger among F&B department employees than among kitchen cooks. In addition, international hotels showed a higher level of employee brand identification than local hotels. Employee brand identification was also affected by hotel brand personality and employee personality. The dimension of 'sincerity' had the strongest effect on brand identification, followed by the dimensions of 'excitement' and 'sophistication'. Especially, when the hotel brand personality was lower than the employee personality at the dimension of 'sincerity', the level of employee brand identification was much lower. Overall, employee brand identification, which is a key factor for successful brand delivery to customer, could be enhanced through strong strategies to improve the brand personality dimensions and enhance employee development.

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Color Space Exploration and Fusion for Person Re-identification (동일인 인식을 위한 컬러 공간의 탐색 및 결합)

  • Nam, Young-Ho;Kim, Min-Ki
    • Journal of Korea Multimedia Society
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    • v.19 no.10
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    • pp.1782-1791
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    • 2016
  • Various color spaces such as RGB, HSV, log-chromaticity have been used in the field of person re-identification. However, not enough studies have been done to find suitable color space for the re-identification. This paper reviews color invariance of color spaces by diagonal model and explores the suitability of each color space in the application of person re-identification. It also proposes a method for person re-identification based on a histogram refinement technique and some fusion strategies of color spaces. Two public datasets (ALOI and ImageLab) were used for the suitability test on color space and the ImageLab dataset was used for evaluating the feasibility of the proposed method for person re-identification. Experimental results show that RGB and HSV are more suitable for the re-identification problem than other color spaces such as normalized RGB and log-chromaticity. The cumulative recognition rates up to the third rank under RGB and HSV were 79.3% and 83.6% respectively. Furthermore, the fusion strategy using max score showed performance improvement of 16% or more. These results show that the proposed method is more effective than some other methods that use single color space in person re-identification.

Development of Standardized Pattern Identification for Dizziness by Delphi Method (현훈(어지럼증) 한의표준변증안 개발을 위한 전문가 델파이 조사)

  • Oh, Se-Hee;Jung, Chan-Yung;Hong, Seung-Ug
    • The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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    • v.33 no.2
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    • pp.43-54
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    • 2020
  • Objectives : The goal of this study is developing standardized pattern identification of dizziness using delphi method. Methods : The pattern identification of dizziness which derived through literature review is studied by delphi method. A group of 9 experts of korean medicine participated in Delphi examination. Experts carried out evaluating and correcting the pattern identification and symptoms by e-mail. Results : Through 3 delphi examinations, final standardized pattern identification of dizziness was suggested. It consisted of 2 items of excess syndrome, 2 items of excess-deficiency combination syndrome, and 3 items of deficiency syndrome. Conclusions : By the delphi examinations among experts, a standardized pattern identification of dizziness was suggested. These pattern identification will contribute to research and treatment of korean medicine. Further study is necessary for modification of pattern identification by practical clinical use.