Applying Dynamic Causal Mining in Retailing
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Summary
- Figure 1 shows two alternative configurations applied for nitrogen removal via nitrite and the 100 selection of PHA storing biomass downstream from the anaerobic digester.
- At the beginning of period 1, the biomass showed a typical feast and famine 238 response (the duration of the feast phase was approximately 16% of the total cycle duration), 239 although the ammonium conversion to nitrite was 36±13%, producing only 6.5 mgNO2-N/L 240 at the completion of the aerobic phase (Figure 2 a and b).
- Furthermore, 72±16% of the PHA was 286 degraded during the aerobic and anoxic famine conditions (Figure 5).
- To cope with the residual ammonium concentration, configuration 2 applied a two stage 299 process for nitritation and selection of PHA storing biomass.
- In general, the low crystallinity in 364 combination with a low Tg (between -1.1 to -0.5°C) indicate biopolymers with amorphous 365 characteristics 14 .
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"Applying Dynamic Causal Mining in R..." refers background in this paper
...The Web is referred to as the " semantic Web " , where information will be retrieve from intelligent network services such as information brokers and search agents [Decker & Melnik, 00, Decker et al., 00]....
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"Applying Dynamic Causal Mining in R..." refers background in this paper
...Data mining is the systematic refining of information resources on the Web for business intelligence [Hackathorn, 00]....
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Frequently Asked Questions (14)
Q2. What is the main part of the DCM algorithm?
The pattern matching part, which focus on matching patterns of graphs, like optional parts, union of patterns, nesting, The solution modifiers part , which allows to modify values applying classical operators like projection, distinct, order, limit, and offset.
Q3. What is the use of support in the pruning?
The support is used as the threshold to eliminate unsatisfactory dynamic sets and to obtain the rules from the satisfactory sets.
Q4. What is the polarity of the new data set?
Let Dnew be a new data set constructed from D. A generalized dynamic association rule is an implication of the form A1 →p A2, where A1 ⊂ D, A1 ⊂ D, A1∩ A2= φ and p is the polarity.
Q5. What is the purpose of the ontology?
It is designed to store and retrieve identities that are constructed from triplex collections of strings (sequences of letters) and can be queried with Sparql.
Q6. What are the common tools for developing ontology?
The most common tools for developing ontology are Protégé-2000 (Protege, 2000), Ontolingua (Ontolingua, 1997), and Chimaera (Chimaera, 2000) as ontology-editing environments.
Q7. What is the goal of the semantic network interface?
And the interface should be able to update the ontologies for improvement, thus rather storing a large amount of information, the relevant ontologies or relations are stored.
Q8. What is the main goal of the DCM process?
It also represents a filtering process that prunes away static attributes, which reduces the size of the data set for further mining.
Q9. What is the definition of the single attribute support?
In this case, the single attribute support is defined to be 0.5, which means that if an attribute with polarity +, -, or 0 occurs in more than half of total time stamps, it will be pruned.
Q10. What is the definition of the Web?
The World Wide Web has evolved into a dynamic, distributed, heterogeneous, complex network, which is hard toIcontrol [Albert et al., 99, Huberman & Adamic, 99].
Q11. What is the purpose of system dynamics?
System dynamics [Sterman 1994 & Coyle, 1996], is a tool to visualize and understand such patterns of dynamic complexity, which is build up from a set of system archetypes based on principles in System thinking [Sterman, 2000].
Q12. What is the main idea of the paper?
This paper has considered the most fundamental ways to tackle the problems caused by information overload and complexity in retailing.
Q13. What is the polarity count of the dynamic sets?
While making a pass, one dynamic set is read at a time and the polarity count of candidates supported by the dynamic sets is incremented.
Q14. What is the meaning of the rule plot?
where association rule generation techniques find surface associations, causal inference algorithms identify the structure underlying such associations.