Results 271 to 280 of about 291,146 (315)
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Journal of PeriAnesthesia Nursing, 1996
The goal of research is to discover new knowledge to improve patient care. Research is essential because of its ability to establish causal relationships. This article discusses the minimum requirements a research report must meet to establish a causal relationship.
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The goal of research is to discover new knowledge to improve patient care. Research is essential because of its ability to establish causal relationships. This article discusses the minimum requirements a research report must meet to establish a causal relationship.
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Causal trees: Interleaving + causality
1990Causal Trees are a variant of Milner's Synchronization Trees with enriched action labels which supply indication of the observable causes of observable actions, thus providing us with an interleaving description of concurrent systems which faithfully expresses causality.
Darondeau Ph, DEGANO, PIERPAOLO
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IEE Proceedings - Systems Biology, 2006
The problem of disentangling complex dynamic systems is addressed, especially with a view to identifying those variables that take part in the essential qualitative behaviour of systems. The author presents a series of reflections about the methods of formalisation together with the principles that govern the global operation of systems. In particular,
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The problem of disentangling complex dynamic systems is addressed, especially with a view to identifying those variables that take part in the essential qualitative behaviour of systems. The author presents a series of reflections about the methods of formalisation together with the principles that govern the global operation of systems. In particular,
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The British Journal for the Philosophy of Science, 2005
Summary: Nancy Cartwright offers an account of causal powers, and argues that it explains some important general features of scientific method. Patricia Cheng argues that this theory is superior as a psychological theory of learning to standard models of conditioning. I extend and develop the theory, and argue that it provides the best explanation of a
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Summary: Nancy Cartwright offers an account of causal powers, and argues that it explains some important general features of scientific method. Patricia Cheng argues that this theory is superior as a psychological theory of learning to standard models of conditioning. I extend and develop the theory, and argue that it provides the best explanation of a
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IEEE Transactions on Multimedia, 2011
Optical flow is a widely used technique for extracting flow information from video images. While it is useful for estimating temporary movement in video images, it only captures one aspect of extracting dominant flow information from a sequence of video images.
Yuya Yamashita +2 more
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Optical flow is a widely used technique for extracting flow information from video images. While it is useful for estimating temporary movement in video images, it only captures one aspect of extracting dominant flow information from a sequence of video images.
Yuya Yamashita +2 more
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Pacific Philosophical Quarterly, 1980
AbstractProvides a critical analysis and comparison of the theories of probabilistic causality offered by Hans Reichenbach I.J. Good and Patrick Suppes. Each of these theories faces some fundamental difficulties. In the end, the author argues that probabilistic causality cannot be explicated in terms of statistical relations among discrete events alone.
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AbstractProvides a critical analysis and comparison of the theories of probabilistic causality offered by Hans Reichenbach I.J. Good and Patrick Suppes. Each of these theories faces some fundamental difficulties. In the end, the author argues that probabilistic causality cannot be explicated in terms of statistical relations among discrete events alone.
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Causal Explanations, Causal Determinism
2003AbstractPeople appeal to hidden, nonobvious features in constructing certain categories. The question that arises is: why should this be? The essentialist position proposes that causes are more important than effects — and causes are more internal, hidden, nonobvious than are effects (at least for natural kinds).
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Synthese, 2002
Conventional Decision Theory takes the expected value of an act \(A\) having outcomes \(0\) in the set \(\mathbf{O}\) as \[ \mathbf{EV}(A) = \sum_{O \in \mathbf{O}}{{\mathbf{PROB}}(O/A)}. \] This doesn't always work. For example, suppose your choice is between smoking and not smoking, but that both a propensity to cancer and the desire to smoke are the
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Conventional Decision Theory takes the expected value of an act \(A\) having outcomes \(0\) in the set \(\mathbf{O}\) as \[ \mathbf{EV}(A) = \sum_{O \in \mathbf{O}}{{\mathbf{PROB}}(O/A)}. \] This doesn't always work. For example, suppose your choice is between smoking and not smoking, but that both a propensity to cancer and the desire to smoke are the
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Synthese, 1987
Abstract In chapters 1 and 2, I argued for a mechanistic theory, but I did not give an argument for a nonexplanatory theory of causation. In this chapter I argue that a theory of causation should not be explanatory—direct causes should not be thought of as exemplifying properties in virtue of which they bring about their effects.
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Abstract In chapters 1 and 2, I argued for a mechanistic theory, but I did not give an argument for a nonexplanatory theory of causation. In this chapter I argue that a theory of causation should not be explanatory—direct causes should not be thought of as exemplifying properties in virtue of which they bring about their effects.
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Strong Causality Conditions and Causal Invertibility
SIAM Journal on Control and Optimization, 1980Various strong causality conditions for linear systems are studied and compared. The relationship between these conditions and the causal invertibility problem is considered.
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