Goods Loading Model Based on Effective Space Method

In this paper, a model-based approach of DC-DC converters dedicated to controller design applications for photovoltaic generators is introduced. The paper provides a mathematic averaging model, based on the state space method for DC-DC converters that is used as an adaptation level in photovoltaic generators. This modeling allows the dynamics of the system to be described by presenting a reliable model to be used for oriented controller design. The two most needed topologies of DC-DC converters are proposed, buck and buck-boost, and an overview of integral state feedback controller design using a model-based approach for a boost converter connected to a photovoltaic generator described in our previous published work is provided. The model-based conception of both converter types is analyzed for optimal use in control-oriented design. The validation of each model is demonstrated by comparative curves represented by a detailed plant model using simscape devices available and implemented in Simulink/Matlab.

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An information retrieval model based on vector space method by supervised learning

Information Processing & Management ◽

10.1016/s0306-4573(01)00053-x ◽

2002 ◽

Vol 38 (6) ◽

pp. 749-764 ◽

Cited By ~ 14

Author(s):

Xiaoying Tai ◽

Fuji Ren ◽

Kenji Kita

Keyword(s):

Information Retrieval ◽

Vector Space ◽

Supervised Learning ◽

Retrieval Model ◽

Model Based ◽

Space Method

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Representation, abstraction, and simple-minded sophisticates

Behavioral and Brain Sciences ◽

10.1017/s0140525x19002942 ◽

2020 ◽

Vol 43 ◽

Author(s):

Peter Dayan

Keyword(s):

Decision Theory ◽

Predictive Coding ◽

Bayesian Decision Theory ◽

Bayesian Decision ◽

Model Based ◽

Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

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Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

Microscopy and Microanalysis ◽

10.1017/s1431927600028968 ◽

2001 ◽

Vol 7 (S2) ◽

pp. 578-579

Author(s):

David W. Knowles ◽

Sophie A. Lelièvre ◽

Carlos Ortiz de Solόrzano ◽

Stephen J. Lockett ◽

Mina J. Bissell ◽

...

Keyword(s):

Image Analysis ◽

Mammary Epithelial Cells ◽

Nuclear Organization ◽

Critical Role ◽

Quantitative Model ◽

Mammary Epithelial ◽

Cell Phenotype ◽

Proliferating Cells ◽

Mitotic Apparatus ◽

Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

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