A Conceptual Graphs Framework for Teaching UML Model-Based Requirements Acquisition

Smart VideoText: a video data model based on conceptual graphs

Multimedia Systems ◽

10.1007/s005300200054 ◽

2002 ◽

Vol 8 (4) ◽

pp. 328-338 ◽

Cited By ~ 11

Author(s):

F. Kokkoras ◽

H. Jiang ◽

I. Vlahavas ◽

A.K. Elmagarmid ◽

E.N. Houstis ◽

...

Keyword(s):

Data Model ◽

Video Data ◽

Conceptual Graphs ◽

Model Based

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A new framework for teaching scientific reasoning to students from application-oriented sciences

European Journal for Philosophy of Science ◽

10.1007/s13194-021-00379-0 ◽

2021 ◽

Vol 11 (2) ◽

Author(s):

Krist Vaesen ◽

Wybo Houkes

Keyword(s):

Scientific Reasoning ◽

Teaching Experience ◽

Anecdotal Evidence ◽

Science Students ◽

Single Sentence ◽

Model Based ◽

Contemporary Science ◽

Framework For Teaching ◽

Ronald Giere ◽

New Framework

AbstractAbout three decades ago, the late Ronald Giere introduced a new framework for teaching scientific reasoning to science students. Giere’s framework presents a model-based alternative to the traditional statement approach—in which scientific inferences are reconstructed as explicit arguments, composed of (single-sentence) premises and a conclusion. Subsequent research in science education has shown that model-based approaches are particularly effective in teaching science students how to understand and evaluate scientific reasoning. One limitation of Giere’s framework, however, is that it covers only one type of scientific reasoning, namely the reasoning deployed in hypothesis-driven research practices. In this paper, we describe an extension of the framework. More specifically, we develop an additional model-based scheme that captures reasoning in application-oriented practices (which are very well represented in contemporary science). Our own teaching experience suggests that this extended framework is able to engage a wider audience than Giere’s original. With an eye on going beyond such anecdotal evidence, we invite our readers to test out the framework in their own teaching.

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FORM: a formal object-oriented requirements model based upon conceptual graphs

[1993] Proceedings IEEE International Conference on Developing and Managing Intelligent System Projects ◽

10.1109/dmisp.1993.248614 ◽

2002 ◽

Cited By ~ 2

Author(s):

P. Ye ◽

J.G. Hughes ◽

I.R. McChesney ◽

D. Glass

Keyword(s):

Object Oriented ◽

Conceptual Graphs ◽

Model Based

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Extensions of Simple Conceptual Graphs: the Complexity of Rules and Constraints

Journal of Artificial Intelligence Research ◽

10.1613/jair.918 ◽

2002 ◽

Vol 16 ◽

pp. 425-465 ◽

Cited By ~ 62

Author(s):

J. F. Baget ◽

M. L. Mugnier

Keyword(s):

Knowledge Representation ◽

Operational Semantics ◽

Polynomial Hierarchy ◽

Conceptual Graphs ◽

Basic Operation ◽

Graph Homomorphism ◽

Model Based ◽

Formal Definitions ◽

Decidability And Complexity

Simple conceptual graphs are considered as the kernel of most knowledge representation formalisms built upon Sowa's model. Reasoning in this model can be expressed by a graph homomorphism called projection, whose semantics is usually given in terms of positive, conjunctive, existential FOL. We present here a family of extensions of this model, based on rules and constraints, keeping graph homomorphism as the basic operation. We focus on the formal definitions of the different models obtained, including their operational semantics and relationships with FOL, and we analyze the decidability and complexity of the associated problems (consistency and deduction). As soon as rules are involved in reasonings, these problems are not decidable, but we exhibit a condition under which they fall in the polynomial hierarchy. These results extend and complete the ones already published by the authors. Moreover we systematically study the complexity of some particular cases obtained by restricting the form of constraints and/or rules.

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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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