• 제목/요약/키워드: T-S model

검색결과 3,812건 처리시간 0.028초

Indirect Adaptive Fuzzy Observer Design

  • Yang, Jong-Kun;Hyun, Chang-Ho;Kim, Jae-Hun;Kim, Eun-Tai;Park, Mignon
    • 한국지능시스템학회논문지
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    • 제14권7호
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    • pp.927-933
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    • 2004
  • This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

Reliability analysis of nuclear safety-class DCS based on T-S fuzzy fault tree and Bayesian network

  • Xu Zhang;Zhiguang Deng;Yifan Jian;Qichang Huang;Hao Peng;Quan Ma
    • Nuclear Engineering and Technology
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    • 제55권5호
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    • pp.1901-1910
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    • 2023
  • The safety-class (1E) digital control system (DCS) of nuclear power plant characterized structural multiple redundancies, therefore, it is important to quantitatively evaluate the reliability of DCS in different degree of backup loss. In this paper, a reliability evaluation model based on T-S fuzzy fault tree (FT) is proposed for 1E DCS of nuclear power plant, in which the connection relationship between components is described by T-S fuzzy gates. Specifically, an output rejection control system is chosen as an example, based on the T-S fuzzy FT model, the key indicators such as probabilistic importance are calculated, and for a further discussion, the T-S fuzzy FT model is transformed into Bayesian Network(BN) equivalently, and the fault diagnosis based on probabilistic analysis is accomplished. Combined with the analysis of actual objects, the effectiveness of proposed method is proved.

IoT 환경을 위한 센서 레지스트리 데이터 모델의 설계 및 구현 (Design and Implementation of Sensor Registry Data Model for IoT Environment)

  • 이석훈;정동원;정현준;백두권
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제5권5호
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    • pp.221-230
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    • 2016
  • 사물인터넷(Internet of Things, IoT) 패러다임이 대두되며 센서의 개체수가 폭발적으로 증가할 것으로 예상됨에 따라 센서 네트워크 및 센서 플랫폼 기술들이 변화되고 있다. 센서 플랫폼 중 하나인 센서 레지스트리 시스템(Sensor Registry System, SRS)은 이기종 센서 네트워크 환경에서 센서 데이터의 일관성 있는 의미 해석을 위하여 센서 메타데이터를 등록하고 관리하는 시스템이다. 하지만 기존의 SRS는 IoT 환경에 적합한 데이터 구조를 지니고 있지 않다. 따라서 이 논문은 IoT 환경에서 센서 정보들을 관리하고 등록하기 위하여 센서 레지스트리 데이터 모델을 제안한다. 기존의 SRS를 개선하기 위하여 시맨틱 센서 네트워크 온톨로지(Semantic Sensor Network Ontology, SSNO)을 분석하고, 이에 기반한 메타모델을 설계한다. 또한 설계한 메타모델을 이용하여 관계형 데이터베이스의 테이블로 구축하고 SRS를 웹 애플리케이션으로 구현한다. 이 논문은 제안하는 센서 레지스트리 데이터 모델의 적합성을 검증하기 위하여 SSNO 및 센서 온톨로지 예제들을 변환하여 제안 모델에 적용한다. 평가 결과 제안 모델이 기존 연구들보다 더 풍부한 의미 표현이 가능함을 보인다.

중년후기 여성의 건강증진행위 모형구축 (A Model for Health Promoting Behaviors in Late-middle Aged Woman)

  • 박재순
    • 여성건강간호학회지
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    • 제2권2호
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    • pp.298-331
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    • 1996
  • Recent improvements in living standard and development in medical care led to an increased interest in life expectancy and personal health, and also led to a more demand for higher quality of life. Thus, the problem of women's health draw a fresh interest nowadays. Since late-middle aged women experience various physical and socio-psychological changes and tend to have chronic illnesses, these women have to take initiatives for their health control by realizing their own responsibility. The basic elements for a healthy life of these women are understanding of their physical and psychological changes and acceptance of these changes. Health promoting behaviors of an individual or a group are actions toward increasing the level of well-being and self-actualization, and are affected by various variables. In Pender's health promoting model, variables are categorized into cognitive factors(individual perceptions), modifying factors, and variables affecting the likelihood for actions, and the model assumes the health promoting behaviors are affected by cognitive factors which are again affected by demographic factors. Since Pender's model was proposed based on a tool broad conceptual frame, many studies done afterwards have included only a limited number of variables of Pender's model. Furthermore, Pender's model did not precisely explain the possibilities of direct and indirect paths effects. The objectives of this study are to evaluate Pender's model and thus propose a model that explains health promoting behaviors among late-middle aged women in order to facilitate nursing intervention for this group of population. The hypothetical model was developed based on the Pender's health promoting model and the findings from past studies on women's health. Data were collected by self-reported questionnaires from 417 women living in Seoul, between July and November 1994. Questionnaires were developed based on instruments of Walker and others' health promotion lifestyle profile, Wallston and others' multidimensional health locus of control, Maoz's menopausal symptom check list and Speake and others' health self-rating scale. IN addition, items measuring self-efficacy were made by the present author based on past studies. In a pretest, the questionnaire items were reliable with Cronbach's alpha ranging from .786 to .934. The models for health promoting behaviors were tested by using structural equation modelling technique with LISREL 7.20. The results were summarized as follows : 1. The overall fit of the hypothetical model to the data was good (chi-square=4.42, df=5, p=.490, GFI=.995, AGFI=.962, RMSR=.024). 2. Paths of the model were modified by considering both its theoretical implication and statistical significance of the parameter estimates. Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data (chi-square =4.55, df=6, p=.602, GFI=.995, AGFI=.967, RMSR=.024). 3. The results of statistical testing were as follows : 1) Family function internal health locus of control, self-efficacy, and education level exerted significant effects on health promoting behaviors(${\gamma}_{43}$=.272, T=3.714; ${\beta}_[41}$=.211, T=2.797; ${\beta}_{42}$=.199, T=2.717; ${\gamma}_{41}$=.136, T=1.986). The effect of economic status, physical menopausal symptoms, and perceived health status on health promoting behavior were insignificant(${\gamma}_{42}$=.095, T=1.456; ${\gamma}_{44}$=.101, T=1.143; ${\gamma}_{43}$=.082, T=.967). 2) Family function had a significance direct effect on internal health locus of control (${\gamma}_{13}$=.307, T=3.784). The direct effect of education level on internal health locus of control was insignificant(${\gamma}_{11}$=-.006, T=-.081). 3) The directs effects of family functions & internal health locus of control on self-efficacy were significant(${\gamma}_{23}$=.208, T=2.607; ${\beta}_{21}$=.191, T=2.2693). But education level and economic status did not exert a significant effect on self-efficacy(${\gamma}_{21}$=.137, T=1.814; ${\beta}_{22}$=.137, T=1.814; ${\gamma}_{22}$=.112, T=1.499). 4) Education level had a direct and positive effect on perceived health status, but physical menopausal symptoms had a negative effect on perceived health status and these effects were all significant(${\gamma}_{31}$=.171, T=2.496; ${\gamma}_{34}$=.524, T=-7.120). Internal health locus and self-efficacy had an insignificant direct effect on perceived health status(${\beta}_{31}$=.028, T=.363; ${\beta}_{32}$=.041, T=.557). 5) All predictive variables of health promoting behaviors explained 51.8% of the total variance in the model. The above findings show that health promoting behaviors are explained by personal, environmental and perceptual factors : family function, internal health locus of control, self-efficacy, and education level had stronger effects on health promoting behaviors than predictors in the model. A significant effect of family function on health promoting behaviors reflects an important role of the Korean late-middle aged women in family relationships. Therefore, health professionals first need to have a proper evaluation of family function in order to reflect the family function style into nursing interventions and development of strategies. These interventions and strategies will enhance internal health locus of control and self-efficacy for promoting health behaviors. Possible strategies include management of health promoting programs, use of a health information booklets, and individual health counseling, which will enhance internal health locus of control and self-efficacy of the late-middle aged women by making them aware of health responsibilities and value for oneself. In this study, an insignificant effect of physical menopausal symptoms and perceived health status on health promoting behaviors implies that they are not motive factors for health promoting behaviors. Further analytic researches are required to clarify the influence of physical menopausal symptoms and perceived health status on health promoting behaviors with-middle aged women.

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NUMERICAL CALCULATION OF TWO FLUID SOLAR WIND MODEL

  • KIM S.-J.;KIM K.-S.;MOON Y.-J.;CRO K.-S.;PARK Y. D.
    • 천문학회지
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    • 제37권1호
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    • pp.55-59
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    • 2004
  • We have developed a two fluid solar wind model from the Sun to 1 AU. Its basic equations are mass, momentum and energy conservations. In these equations, we include a wave mechanism of heating the corona and accelerating the wind. The two fluid model takes into account the power spectrum of Alfvenic wave fluctuation. Model computations have been made to fit observational constraints such as electron($T_e$) and proton($T_p$) temperatures and solar wind speed(V) at 1 AU. As a result, we obtained physical quantities of solar wind as follows: $T_e$ is $7.4{\times}10^5$ K and density(n) is $1.7 {\times}10^7\;cm^{-3}$ in the corona. At 1 AU $T_e$ is $2.1 {\times} 10^5$ K and n is $0.3 cm^{-3}$, and V is $511 km\;s^{-1}$. Our model well explains the heating of protons in the corona and the acceleration of the solar wind.

Machine Learning-based Detection of DoS and DRDoS Attacks in IoT Networks

  • Yeo, Seung-Yeon;Jo, So-Young;Kim, Jiyeon
    • 한국컴퓨터정보학회논문지
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    • 제27권7호
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    • pp.101-108
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    • 2022
  • 본 논문은 다수의 사물인터넷 단말에서 보편적으로 수집할 수 있는 시스템 및 네트워크 메트릭을 학습하여 각 사물의 경험데이터를 기반으로 서비스거부 및 분산반사 서비스거부 공격을 탐지하는 침입 탐지 모델을 제안한다. 먼저, 공격 시나리오 유형별로 각 사물에서 37종의 시스템 및 네트워크 메트릭을 수집하고, 이를 6개 유형의 머신러닝 모델을 기반으로 학습하여 사물인터넷 공격 탐지 및 분류에 가장 효과적인 모델 및 메트릭을 분석한다. 본 논문의 실험을 통해, 랜덤 포레스트 모델이 96% 이상의 정확도로 가장 높은 공격 탐지 및 분류 성능을 보이는 것을 확인하였고, 그 다음으로는 K-최근접 이웃 모델과 결정트리 모델의 성능이 우수한 것을 확인하였다. 37종의 메트릭 중에는 모든 공격 시나리오에서 공격의 특징을 가장 잘 반영하는 CPU, 메모리, 네트워크 메트릭 5종을 발견하였으며 큰 사이즈의 패킷보다는 빠른 전송속도를 갖는 패킷이 사물인터넷 네트워크에서 서비스거부 및 분산반사 서비스거부 공격 특징을 더욱 명확히 나타내는 것을 실험을 통해 확인하였다.

불확실한 비선형 시스템의 균형화된 모델축소 (A Balanced Model Reduction for Uncertain Nonlinear Systems)

  • 류석환;최병재
    • 한국지능시스템학회논문지
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    • 제16권2호
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    • pp.144-149
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    • 2006
  • 이 연구는 T-S 퍼지 접근법을 이용하여 불확실한 비선형 시스템의 균형화된 모델 차수 축소 방법을 제시한다. 일반화된 가제어성, 가관측성 그래미안을 정의하고 이들을 이용하여 균형화된 상태공간 모델을 얻는다. 균형화된 상태공간 모델로부터 상태변수 뿐만 아니라 불확실한 요소를 절삭하여 간략화된 모델을 얻는 기법을 제시하고 모델오차의 상한치를 제시한다. 균형화된 상해공간은 선형행렬 부등식의 해를 구하여 구현할 수 있으며 제시한 방법의 효용성을 보여주기 위하여 수치 예를 보여준다.

Power t distribution

  • Zhao, Jun;Kim, Hyoung-Moon
    • Communications for Statistical Applications and Methods
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    • 제23권4호
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    • pp.321-334
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    • 2016
  • In this paper, we propose power t distribution based on t distribution. We also study the properties of and inferences for power t model in order to solve the problem of real data showing both skewness and heavy tails. The comparison of skew t and power t distributions is based on density plots, skewness and kurtosis. Note that, at the given degree of freedom, the kurtosis's range of the power t model surpasses that of the skew t model at all times. We draw inferences for two parameters of the power t distribution and four parameters of the location-scale extension of power t distribution via maximum likelihood. The Fisher information matrix derived is nonsingular on the whole parametric space; in addition we obtain the profile log-likelihood functions on two parameters. The response plots for different sample sizes provide strong evidence for the estimators' existence and unicity. An application of the power t distribution suggests that the model can be very useful for real data.

Influence diagnostics for skew-t censored linear regression models

  • Marcos S Oliveira;Daniela CR Oliveira;Victor H Lachos
    • Communications for Statistical Applications and Methods
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    • 제30권6호
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    • pp.605-629
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    • 2023
  • This paper proposes some diagnostics procedures for the skew-t linear regression model with censored response. The skew-t distribution is an attractive family of asymmetrical heavy-tailed densities that includes the normal, skew-normal and student's-t distributions as special cases. Inspired by the power and wide applicability of the EM-type algorithm, local and global influence analysis, based on the conditional expectation of the complete-data log-likelihood function are developed, following Zhu and Lee's approach. For the local influence analysis, four specific perturbation schemes are discussed. Two real data sets, from education and economics, which are right and left censoring, respectively, are analyzed in order to illustrate the usefulness of the proposed methodology.

Development of ML and IoT Enabled Disease Diagnosis Model for a Smart Healthcare System

  • Mehra, Navita;Mittal, Pooja
    • International Journal of Computer Science & Network Security
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    • 제22권7호
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    • pp.1-12
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    • 2022
  • The current progression in the Internet of Things (IoT) and Machine Learning (ML) based technologies converted the traditional healthcare system into a smart healthcare system. The incorporation of IoT and ML has changed the way of treating patients and offers lots of opportunities in the healthcare domain. In this view, this research article presents a new IoT and ML-based disease diagnosis model for the diagnosis of different diseases. In the proposed model, vital signs are collected via IoT-based smart medical devices, and the analysis is done by using different data mining techniques for detecting the possibility of risk in people's health status. Recommendations are made based on the results generated by different data mining techniques, for high-risk patients, an emergency alert will be generated to healthcare service providers and family members. Implementation of this model is done on Anaconda Jupyter notebook by using different Python libraries in it. The result states that among all data mining techniques, SVM achieved the highest accuracy of 0.897 on the same dataset for classification of Parkinson's disease.