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Knowledge causal

Relationships Between Objects, Processes, and Events. Relationships can be causal, eg, if there is water in the reactor feed, then an explosion can take place. Relationships can also be stmctural, eg, a distiUation tower is a vessel containing trays that have sieves in them or relationships can be taxonomic, eg, a boiler is a type of heat exchanger. Knowledge in the form of relationships connects facts and descriptions that are already represented in some way in a system. Relational knowledge is also subject to uncertainty, especiaUy in the case of causal relationships. The representation scheme has to be able to express this uncertainty in some way. [Pg.531]

The overall conclusion that can be drawn from a survey of CPI data collection systems is that the better systems do attempt to address the causes of human error. However, because of the lack of knowledge about the factors which influence errors, the causal information that is collected may not be very useful in developing remedial strategies. General information in areas such as severity, work control aspects and the technical details of the incident will be required in all data collection systems. However, in almost all cases a structured process for causal analysis is lacking. Some of the requirements for causal analysis are set out in the following sections. [Pg.262]

Gobert, J. D., Clement, J. J. (1999). Effects of student-generated diagrams versus studentgenerated summaries on conceptual understanding of causal and dynamic knowledge in plate tectonics. Journal of Research in Science Teaching, 56(1), 39-53. [Pg.189]

Systematic analysis. The data must be systematically analyzed to gain insight regarding the associations between various treatments and medical conditions. This knowledge can assist in causality assessments. [Pg.653]

Causality requires that the filter response at time n be computed on the basis of present and past information and not require knowledge of either the future input or output. Thus, the computation of zm (n) involves only present and past (values of the) inputs and only past outputs. [Pg.14]

In most expert systems, only small sections of the information in the knowledge base are causal. Causal knowledge consists of statements of facts and relationships, linked to information that explains why these facts are true. The "why" part is often not required for the ES to function effectively and, therefore, not included in a working ES. [Pg.212]

Note This table is not meant to be quantitative and is based on a general knowledge of these drugs. It is very difficult to determine incidence, and it can also be difficult to determine causality, especially with most case reports. [Pg.461]

Other, often made distinction in types of research, are between exploration, description, explanation, and testing, van der Zwaan (Zwaan van der, 1990). Exploration is conducted when theoretical knowledge in literature lacks information on which variables are important. Description types of research aim at the relevance of the variables. Explanation types of research aim at identifying the causal links between variables and phenomena. Finally, testing types of research aim at proving the hypotheses derived from the causal links. The research project discussed in this thesis is mainly explorative in nature. The emphasis is to design concepts and a protocol, which increases the understanding of the problem of how and why accidents continue to occur in companies in the chemical process industry. In this way a contribution to the solution of the problem will be made and consequently this research can be typified as applied positivistic exploratory research. [Pg.35]

Incident data in Section 3.0 show that more than half of the reactive incidents, where some causal information is available, are attributed to inadequate operating procedures and training. These data illustrate the challenge of effectively communicating a practical, working knowledge of an often complex array of chemical and process information. [Pg.343]

What must be remembered is that while the twentieth-century definition of "philosophy" is broad and flexible, eighteenth- and early-nineteenth-century notions of philosophy more narrowly identified philosophy with unified systems of causal demonstration. Natural philosophy was nothing if not causal, and it was oriented to strongly probable, or certain, knowledge. 26... [Pg.81]

Definition of Axiomatic Theories. An axiomatic theory is an attempt to formalize an intuitive theory. Geometry was intuitive before Euclid wrote "The Elements . An intuitive theory is defined as a body of knowledge which attempts to express relationships and causality between objects, but is not formal. Most modern science is still intuitive, even though it may represent many of it s findings in exact mathematical formulae. As long as the entire corpus of knowledge is not expressed in a single formal system, it will remain intuitive. [Pg.194]

Based on this evidence, the odds that a toxic release caused the flshkill is a convincing 108 to 1. The level of belief is now sufficiently high for a reasonable person to take regulatory action. Bayes theorem allowed optimal use of evidence to define the belief warranted in the causal hypothesis that a toxic release caused the flshkill evidence changed our state of knowledge about the flshkill. [Pg.79]


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