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Using this table, you can see the definitions of the views in the database. As with many mainstream DBMS products, information about views is tightly linked to the information about tables in the DB2 catalog. This means you often have more than one way to find the answer to a catalog inquiry. For example, here is a direct query against the DB2 VIEWS system table to obtain the names and creators of all views defined in the database: List the views de ned in the database.

FIGURE 19.12 Side-leakage ratio versus Sommerfeld number for full and partial journal bearings, L/D = 1, Swift-Stieber boundary conditions. (From Raimondi and Boyd [19.7].)

SELECT DISTINCT VIEWSCHEMA, VIEWNAME, DEFINER FROM SYSCAT.VIEWS;

For slenderness ratios other than the four displayed ( , 1, 1 2, and 1 4), Raimondi and Boyd suggest the use of the following interpolation formula: yL/D = D L

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Note the use of DISTINCT to eliminate duplicate rows that would be present for views with long text definitions in older versions of DB2. Perhaps an easier way to obtain the same information is to query the DB2 TABLES system table directly, selecting only rows representing views, as indicated by the TYPE value: List the views de ned in the database.

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vant inverse transform. In a streaming application, the matrix selection data could add a significant bandwidth overhead to the streaming transmission, thereby somewhat defeating the original reason for compressing the video in the first place. A practical compromise is the discrete cosine transform (DCT). This transform matrix is constant and is suitable for a variety of images; it is sometimes referred to as quick KLT. Other transforms that can be used in data compression include the popular discrete wavelet transform (DWT) and the less-commonly used discrete Hartley transform (DHT), the slant transform, the Haar transform, and the Hadamard transform [3]. The DCT is a close relative of the discrete Fourier transform (DFT), which is widely used in quadrature signal analysis. Similar to DFT techniques, DCT offers a reliable algorithm for the quick execution of matrix multiplication. The main advantage of DCT is that it decorrelates the pixels efficiently; put another way, it efficiently converts statistically dependent pixel values into independent coefficients. In so doing, DCT packs the signal energy of the image block onto a small number of coefficients. Another significant advantage of DCT is that it makes available a number of fast implementations. A block diagram of the DCT-based coder is shown in Figure E.1.

where y = any performance variable, that is, (R/C)(f ), h0 /C, etc., and the subscript of y is the L/D value at which the variable is being evaluated. For partial bearings with bearing arc angles other than the three displayed (180 , 120 , and 60 ), Raimondi and Boyd recommend using the following interpolation formula: y = 1 [( 120)( 60)y180 2( 180)( 60)y120 + ( 180)( 120)y60] 7200

SELECT TABSCHEMA, TABNAME, DEFINER FROM SYSCAT.TABLES WHERE TYPE = 'V';

where y = any performance variable and the subscript of y is the at which the variable is being evaluated. Some of the tedium associated with use of charts can be removed by employing curve fits of the data. Seireg and Dandage [19.8] have developed approximate equations for the full journal bearing data of the Raimondi and Boyd charts. Table 19.15 gives the coefficients to be used in these curve-fitted equations.

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