Model based prioritization of urban space for the development of municipal services in Chandernagore Municipal Corporation (CMC), India

This paper from the perspective of the Neighbor cellular space, Proposed a new urban space expansion model based on a new multi-objective gray decision and CA. The model solved the traditional cellular automata conversion rules is difficult to meet the needs of the inner space-time analysis of urban changes and to overcome the problem of uncertainty in the combination of urban drivers and urban cellular automata. At the same time, the study takes Pidu District as a research area and carries out urban spatial simulation prediction and analysis, and draws the following conclusions: (1) The design idea of the urban spatial expansion model proposed in this paper is that the urban driving factor and the neighborhood function are tightly coupled by the multi-objective grey decision method based on geographical conditions. The simulation results show that the simulation error of urban spatial expansion is less than 5.27&thinsp;%. The Kappa coefficient is 0.84. It shows that the model can better capture the inner transformation mechanism of the city. (2) We made a simulation prediction for Pidu District of Chengdu by discussing Pidu District of Chengdu as a system instance.In this way, we analyzed the urban growth tendency of this area.presenting a contiguous increasing mode, which is called "urban intensive development". This expansion mode accorded with sustainable development theory and the ecological urbanization design theory.

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Semantic User Model Inferences for Travel Recommender Systems

Tourism Informatics ◽

10.4018/978-1-60566-818-5.ch002 ◽

2010 ◽

pp. 23-37

Author(s):

Yanwu Yang

Keyword(s):

Recommender Systems ◽

Urban Space ◽

Web Application ◽

Description Logic ◽

User Model ◽

Model Based ◽

Travel Recommender Systems ◽

Spatial Entities

This chapter proposes a semantic user model based on a description logic language to represent user’s knowledge and information, and a set of domain-dependent rules specific to the tourism domain in terms of spatial criteria (i.e., distance) and cognition to infer useful user features such as interests and preferences as important inputs for travel recommender systems (TRS). We also identify a spatial Web application scenario in the tourism domain, which is intended to provide personalized information about a variety of spatial entities in order to assist the user in traveling in an urban space.

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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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