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This chapter discusses the characterization of U.S. businesses and government agencies based on solid waste stream composition percentages. The purpose of characterization was to determine and group the business types that generate similar solid waste materials. Figure 15.1 displays the characterization process. Standard Industrial Classi cation (SIC) codes were used as the grouping basis to describe types of business functions, as described in Chap. 14. The waste records gathered from each SIC code group were consolidated and the mean and variance waste composition percentages were calculated for each material. SIC code groups have historically been used by U.S. environmental regulators to classify businesses based on solid waste generation. The usage of SIC codes for this purpose was statistically validated and is discussed in Sec. 15.3 of this chapter. After the successful validation of using SIC codes, multivariate cluster analysis was conducted on the SIC code group waste composition data to reduce groups further. Twenty-two of these nal clusters, referred to as waste groups, were formed that statistically generate similar compositions of solid waste. In the next chapter, these waste groups are analyzed to determine the signi cant variables that in uence annual solid waste quantities.

CAUTION: We don t recommend checking this option because it will take up all the space in your iPad and leave no room for all those cool apps! c. Now check off any of the playlists or artists in the two columns on the bottom of the screen. You can even use the Search box at the top of the Artists column to search for particular artists.

Several preparations were completed before beginning the solid waste characterization process and waste group determination. Speci cally, the 438 waste records (companies) collected from the national survey included 65 SIC code groups. Each waste record was placed in 1 of 65 data matrices; with each matrix representing each of the 65 SIC code

Class Members In lines 16 and 17, we declare two class variables. The first is the reference to the ORB we are going to use and the second is a reference to the server on which we are going to invoke two methods.

Purpose Reduce 438 businesses and government agencies into their 65 SIC code groups Characterize 65 groups using standardized parameters (means and standard deviations)

When you click the Movies tab, you can choose to sync specific, recent, or unwatched movies, or all of them. To sync movies from your computer to your iPad, follow these steps. 1. 2. 3. 4. Connect your iPad to your computer, start iTunes software, and click on your iPad in the left nav bar. Click the Movies tab on the top of the main window. Check the box next to Sync Movies (see Figure 3 26). If you would like to sync recent or unwatched movies, then check the box next to Automatically include and use the pull-down to select All, 1 most recent, All unwatched, 5 most recent unwatched, etc.

Conduct multivariate cluster analysis on population parameters to reduce data groups by clustering similar SIC code groups

Main Method and Class Instantiation Every Java program has a main method with standard signature. We declare the main method in the usual way and then initialize our ORB. Next, we instantiate the SavingAccountClient class (see lines 19 24). Obtaining a Reference to the Server In lines 26 43, we obtain a reference to the server by using the naming service. This code is similar to the code on the server side, so it will not be explained further. The code is enclosed in a try/catch block in order to deal with any exceptions that may be thrown in the process of obtaining the reference to the server class. Invoking Methods on the Server

Reduce to 22 clusters (waste groups)

If you selected any item besides All, then you have the choice to sync specific movies or videos to your iPad. Simply check the boxes next to the movies you would like to include in the sync (see Figure 3 27).