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For pairs of variables measured on an interval or ratio scale, a correlation coef cient (r) can be calculated. This value quanti es the linear relationship between the variables. It generates values ranging from 1:0 to 1:0. If an optimal straight line is drawn through the points on a scatterplot, then the value of r re ects how close to this line the points lie. Positive numbers indicate a positive correlation and negative numbers indicate a negative correlation. If r is around 0 then there appears to be little or no relationship between the variables. For example, three scatterplots illustrate different values for r as shown in Figure 5.22. The rst graph illustrates a good positive correlation, the second graph shows a negative correlation and the third graph illustrates a poor correlation. The formula used to calculate r is shown here:

18: Introducing CORBA 8. The client also creates a name component to query the naming context about that particular object reference. 9. The naming context then resolves the name component and returns the object. As the type of the returned object is generic, the object is converted to a specific object reference with the help of its Helper class. 10. Now the client can invoke the methods on that particular object and perform all the operations. Note that in Java, the naming service used is known as the COS Naming Service. All necessary interfaces required to be able to use this naming service are available in a package called org.omg.CosNaming. CORBA applications in Java need to import this package in order to use the naming service. The following example, which creates an object reference name binding using Naming Services, may help you understand Naming Services better. First, assume the existence of a CORBA application called Welcome, which welcomes a new user with the message "Welcome to CORBA." Consider the steps the server performs to add the object reference binding in the naming service: 1. Implement the interface. Assume that the implementation already exists:

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what they will do next. We guess what someone is trying to communicate to us and then predict what she will say next.

amss (J from 2000)

signal and the event gains more and more value In this way our brain learns to attach a value to all the events and objects and places around us Many will remain neutral, but some will acquire high value and some will acquire low value We experience this map of values within our brain when we return from a long trip abroad we feel a rising emotional response as the streets we are moving through become more and more familiar If we approached the things with high value and avoided the things with low value, we would obtain rewards and avoid punishments But this associative learning mechanism tells us only which things are valuable It doesn t tell us how to get these valuable things.

Flavourful, easy, and quick to prepare, here is another true Indian dish. This one comes from one of Cynthia s dietetic interns, Ruby Ubhi. Preparation Time: 15 minutes Cooking Time: 20 to 25 minutes Yield: 4 servings 19 oz (540 ml) can of chickpeas 3 cloves garlic, minced 11 2 tbsp (22 ml) canola oil 1 medium onion, finely chopped 1 tsp (5 ml) ginger, grated 1 large tomato, chopped

Easily move data between Excel and Access Store Excel data in a structured, relational database Use Excel pivot tables with Access data Report Access data using the Excel presentation layer Move data between Excel and Access using VBA, ADO and SQL

Thorndike s cat, when rst put in the puzzle box, knows that the sh is valuable, but it doesn t know what to do to get the sh A mechanism for learning exactly what to do to get rewards (or avoid punishments) also exists It s called the temporal difference (TD) algorithm This procedure allows a machine to discover the best sequence of actions to perform in order to get something of value This procedure is also known as the Actor Critic model One part of the program, the Actor, chooses the next action to perform The other part of the program, the Critic, indicates how good this action was This critic tells the actor about any errors in the prediction A good action is one in which the situation we are in now has a value that is higher than the situation we were in before performing the action.

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