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styles that exist in the normal population and came up with three sets of personality variables to define and measure them. The first set, termed motivating aims, represents his three basic axes in evolutionary form. The original pleasure-pain polarity was called enhancing-preserving, active-passive was named modifying-accommodating, and otherself was labeled individuating-nurturing. The second set of variables, borrowed from Carl Jung (1936/1971), was termed cognitive modes. For T. Millon, cognition means an individual s primary source of obtaining information and the means by which that information is processed or transformed. Preferred sources of information can be the self (internal) or others (external) and either tangible or intangible. Favored methods of transforming information can be intellectual or affective and assimilative versus imaginative. The last set of variables describes 10 common interpersonal behaviors or styles (T. Millon, 1994, 2004). Eight of the 10 styles (i.e., personalities) are essentially the same as those measured by the MAPI, MBHI, and PACL and are empirically related to PDs (see Table 20.1 under the column heading MIPS/ MIPS-R). Two additional behavioral patterns, controlling/dominant and yielding/submissive, are conceptually related to sadistic and self-defeating PDs and are also found in two recently developed measures, the Millon Inventory of Diagnostic Criteria (MIDC; Immelman, 1999) and Millon Behavioral Medicine Diagnostic (MBMD; T. Millon et al., 2001).



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Figure 1.12 Characteristic examples of aerosol particle size distribution and chemical composition in urban (top) and high Alpine air (bottom). Graphs (left): number size distribution function dN/d(log d p) (symbols and error bars: arithmetic mean values and standard deviations, ELPI, * SMPS, characteristic particle size modes). Pie charts (right): typical mass proportions of main components. (Reproduced from [74] with permission from Wiley-VCH Verlag.)





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Before trigger, 106 Binary relationship types, 400 Bit vectors, 165, 173 Blind write, 192, 238 Block ciphers, 359, 378 Blocking calls, 560 Blocking messaging, 563 Blocking, 617 Bloom vectors, 165, 173 Bond Contribution Calculation, 54 62 for (C0, C3, C1) ordering, 55 clustered af nity matrix, 57 partial clustered af nity matrix, 56 Bond Energy Algorithm (BEA), 53, 78 Bottom up design approach, 35, 37, 78 Bottom up methodology, 459 461, 509 Boyce Codd normal form (BCNF), 446 Broadcast approach, 283, 292 Brute force attack, 359, 378 Business Services Tier, 538 540, 574

I certainly don t claim that this survey represents the views of all spreadsheet users, and it s likely that the results would be different if I did the survey today. But I find it interesting, and maybe you will, too. I discuss my interpretations of this data in the following sections.

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Therefore, the MAP estimate for churn is false for each combination of International Plan and VoiceMail Plan membership. This result does not appear to be very helpful, since we will predict the same outcome for all customers regardless of their membership in the plans. However, not each of the classi cations has the same strength of evidence. Next, we consider the level of evidence in each case, as de ned by the posterior odds ratio. The posterior odds ratio represents a measure of the strength of evidence in favor of a particular classi cation and is calculated as follows.

measure physical activity because of the confounding aspects of the cognitive recall process (Durante & Ainsworth, 1996) Questionnaires validated against biological estimates of activity (eg, metabolic tolerance) are useful in dichotomizing between high-active and sedentary individuals, but they are less accurate in providing valid data for other aspects of behavior, such as distinguishing among levels of activity intensity Measurement of physical activity by accelerometry has become popular, but accelerometry has practical limitations (Ward, Evenson, Vaughn, Rodgers, & Troiano, 2005) Poor measurement can compound difficulties in evaluating exercise adherence, but consistent and clear measurement of adherence and dropout are not characteristic of the exercise and physical activity literature In supervised exercise studies, widely varying definitions and variables are used to indicate adherence This makes it difficult to compare the effectiveness of different interventions.

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Multimedia services, such as streaming applications, are growing in popularity with advances in compression technology, high-bandwidth storage devices, and highspeed access networks. Streaming services are generally used in applications like multimedia information and message retrieval, video on demand, and pay TV. Also, there has been growing popularity of portable devices, such as notebook computers, PDAs, and mobile phones in recent years. Now it is possible to provide very high-speed access to portable devices with emerging technologies like WLAN and 3G networks. For instance, emerging 3G wireless technologies provide data rates of 144 kbps for vehicular, 384 kbps for pedestrian, and 2 Mbps for indoor environments [1,2]. Hence, it is now possible to enrich the end user s experience by combining multimedia services [3,4] with mobile-speci c services such as geographic positioning, user pro ling, and mobile payment. One example of such service is mobile cinema ticketing, which uses geographic positioning and user-de ned

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