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Each of the six HG/HI companies knows how to focus and to create vigorous energy around its core products and services. Each one also, in addition to being incredibly focused, has a continuity of equally focused leaders. Among the six benchmark companies, Wal-Mart, the largest retailer in the world, takes first prize for top-line growth. It has such an enormous focus on growth that people don t know whether to love Wal-Mart for its low prices or hate it for the empire that it has developed, which scares competitors and sometimes suppliers. Regardless of what people may think about it, it is hard not to admire the fact that Wal-Mart excels in its ability to focus on top-line growth. The company is so ruthlessly efficient that 4 percent of the growth in the U.S. economy s productivity from 1995 to 1999 was due to Wal-Mart alone, researchers at the McKinsey Global Institute estimated last year. No other single company has had as measurable an impact. Wal-Mart also has forced competitors to become more efficient, driving the nation s productivity output per hour of work even higher. (Goldman and Cleeland, An Empire Built on Bargains ) We discovered that when our HG/HI companies lost focus, they also lost ground in top-line growth. BMW s acquisition of Britain s MG Rover group in 1994 caused it to experience significant brand and marketing challenges, which cost it revenue and growth. But BMW knew that topline growth through the strength of its products was the most important

The method for the determination of limiting molar conductivities of electrolytes KI was discussed in Section 7.1. The limiting molar conductivities of individual ions kI can be obtained by the following methods. i

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1. Biederman I, Ju G. Surface versus edge-based determinants of visual recognition. Cogn Psychol 1988;20:38 64. 2. Bober M. MPEG-7 visual shape descriptors. IEEE Trans Circuits Syst Video Technol 2001;11(6):716 719. 3. Bogaert J, Rousseau R, Van Hecke P, Impens I. Alternative area perimeter ratios for measurement of 2D-shape compactness of habitats. Appl Math Comput 2000;111:71 85. 4. Bowman ET, Soga K, Drummond T. Particle shape characterization using Fourier analysis. Geotechnique 2001;51(6):545 554. 5. Boxer L. Computing deviations from convexity in polygons. Pattern Recog Lett 1993;14:163 167. 6. Brady M, Yuille AL. An extremum principle for shape from contour. IEEE Trans Pattern Anal Mach Intell 1984;6(3):288 301. 7. Bribiesca E. Measuring 2D shape compactness usng the contacct perimeter. Pattern Recog 1997;33(11):1 9. 8. Chan TM. Approximating the diameter, width, smallest enclosing cylinder, and minimumwidth annulus. Int J Comput Geom Appl 2002;12(1 2):67 85. 9. Chang JS, Yap CK. A polynomial solution for the potato-peeling problem. Discrete Comput Geom 1986;1:155 182. 10. Chaudhuri J, Nandy SC, Das S. Largest empty rectangle among a point set. J Algorithms 2003;46(1):54 78.

The basic principle behind HARQ for HSUPA is the same as that for HSDPA. After each transmitted TTI the Node B indicates to the transmitting UE whether the packet was received correctly or not. In the event of incorrect reception the UE will retransmit the packet. The Node B tries to recover the packet by combining the energy of the retransmission with previous transmissions until the packet is received correctly or the maximum number of retransmissions is reached. The HSUPA HARQ may either use Chase combining where each retransmission is an exact copy of the initial transmission, or incremental redundancy where retransmissions contain additional redundancy bits for the initially transmitted bits. The main di erences between HARQ with HSUPA and HARQ with HSDPA are that HSUPA HARQ is fully synchronous and, with incremental redundancy, even transmitted redundancy versions can be predetermined; it also operates in soft handover. HARQ for HSUPA is discussed in more detail later in this chapter.

The exact size depends on the server. The behavior of the buffer when full is indicated by the value of the autoFlush attribute, which is described in the next section. The default value of the buffer attribute depends on the server implementation.

$ mutt -s My Fedora Version -a /etc/redhat-release \ chris@example.com < email-body.txt $ mutt -s My Fedora Version -a /etc/redhat-release \ chris@example.com < /dev/null

The data and the analysis do not change. If our interest is in this new quantity, we simply replace the original owgraph MGF of (7.16) with this one (7.27) and perform the analysis as before. Thus, we can take data on the original owgraph and make inferences about any quantity within the owgraph. This owgraph allows for a return to state 1 starting in 1. If our interest were in direct transition from 2 4, returns to state 1 would not be allowed. In this case, we would not include the loop transmittance l1 (s). The probability p23 is set to 1 and the MGF is M(s) = (1 p32 )M23 (s)M34 (s) . 1 p32 M23 (s)M32 (s) (7.28)

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DOWNSIZING: WHEN IT DOES AND DOES NOT WORK Downsizing at its worst perhaps is best represented by Albert Chainsaw Al Dunlap, who had a penchant for a clear-cut approach to job cuts and undertook his final downsizing effort at Sunbeam Corporation. Dunlap s goal was to lift the

new old where Wk;j is the new weight to be computed, Wk; j the old weight attached to the connection between Sk and problem Prj, and Z the learning rate. The weights attached between the feature value layer and the problem layer is computed in a similar manner.

The StatementBean class contains code to perform the actual database connect through a superclass called SQLBean. The code for SQLBean is shown in Listing 10-6. Listing 10-6: Code for SQLBean.java package chapter10 ; import java.sql.*; import java.io.*; public class SQLBean { private String myDriver = "sun.jdbc.odbc.JdbcOdbcDriver"; private String myURL = "jdbc:odbc:stock"; protected Connection myConn; public SQLBean() {} public void makeConnection() throws Exception { Class.forName( myDriver); myConn = DriverManager.getConnection(myURL); }

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