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which can be converted by Gaussian elimination (the general form of the process introduced in Example 3.3) into a matrix of systematic form 1 1 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 0 0 0 G1 = 1 0 0 0 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 where it is seen that the sum of any number of rows results in a codeword with an even number of 1 s. The generator polynomial g2 (X ) = 1 + X + X 3 corresponds to a cyclic Hamming code, as introduced in Example 3.2. The generator polynomial g3 (X ) = 1 + X 2 + X 3 is also the generator polynomial of a cyclic Hamming code whose generator matrix in systematic form is equal to 1 0 1 1 0 0 0 1 1 1 0 1 0 0 G3 = 1 1 0 0 0 1 0 0 1 1 0 0 0 1 In this generator matrix, the submatrix P has at least two 1 s in each row, which makes it a generator matrix of a Hamming code Cb (7, 4). Both the generator polynomials g4 (X ) = (1 + X )(1 + X + X 3 ) = 1 + X 2 + X 3 + X 4 and g5 (X ) = (1 + X )(1 + X 2 + X 3 ) = 1 + X + X 2 + X 4 generate cyclic codes Ccyc (7, 3). Finally, the generator polynomial g6 (X ) = (1 + X + X 3 )(1 + X 2 + X 3 ) = 1 + X + X 2 + 3 X + X 4 + X 5 + X 6 corresponds to a repetition code Ccyc (7, 1) with a generator matrix of the form G7 = 1 1 1 1 1 1 1
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There have been a number of studies on characterizing user access patterns. They can be classi ed into two general categories: (1) studies on wireline users access patterns and (2) studies on wireless users access patterns. In this section, we review the work in both areas. 5.2.1 Wireline User Workload Characterization
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modes of thinking, feeling, and behaving. Thus, a reciprocal and synergistic model is proposed. One effective CB interviewing and intervention technique is the introduction of self-monitoring records of symptoms, feelings, thoughts, and actions. Such daily diaries are useful diagnostically and clinically. They have the potential of demonstrating to the clinician and the patients the patterns of maladaptive thinking and pain behaviors that may be contributing to their pain experience. Self-monitoring records can be used for many purposes, such as allowing the therapist to know when are-ups occur; identifying the precedents and antecedents of painful episodes; and determining target behaviors, thoughts, and feelings that should be addressed during therapy sessions. There are ve central assumptions that characterize the CB approach (summarized in Table 13.2). The rst assumption is that all people are active processors of information rather than passive reactors to environmental contingencies. People attempt to make sense of the stimuli from the external environment by ltering information through organizing attitudes derived from their prior learning histories and by general strategies that guide the processing of information. People s responses (overt as well as covert) are based on these appraisals and subsequent expectations and are not totally dependent on the actual consequences of their behaviors (i.e., positive and negative reinforcements and punishments). From this perspective, anticipated consequences are as important in guiding behavior as are the actual consequences. A second assumption of the CB approach is that one s thoughts (e.g., appraisals, attributions, and expectations) can elicit or modulate affect and physiological arousal, both of which may serve as impetuses for behavior. Conversely, affect, physiology, and behavior can instigate or in uence thinking processes. Thus, the causal priority depends on where in the cycle the person chooses to begin. Causal priority may be
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p(X) . (2.27) q(X) In the above de nition, we use the convention that 0 log 0 = 0 and the 0 0 convention (based on continuity arguments) that 0 log q = 0 and p log p = 0 . Thus, if there is any symbol x X such that p(x) > 0 and q(x) = 0, then D(p||q) = . We will soon show that relative entropy is always nonnegative and is zero if and only if p = q. However, it is not a true distance between distributions since it is not symmetric and does not satisfy the triangle inequality. Nonetheless, it is often useful to think of relative entropy as a distance between distributions. We now introduce mutual information, which is a measure of the amount of information that one random variable contains about another random variable. It is the reduction in the uncertainty of one random variable due to the knowledge of the other. = Ep log De nition Consider two random variables X and Y with a joint probability mass function p(x, y) and marginal probability mass functions p(x) and p(y). The mutual information I (X; Y ) is the relative entropy between
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interested in all of these aspects of clinical psychology. Many people cynically believe that those who wish to become clinical psychologists are primarily interested in solving their own personal or family problems. Although some studies have indeed suggested that psychologists enter the field in order to help resolve personal or family conflicts or problems (Elliott & Guy, 1993; Guy, 1987; Sussman, 1992), other studies have found little or no association with personal and family problems and choice of psychology as a profession (R. Murphy & Halgin, 1995; Norcross & Guy, 1989). Although numerous terminal master s degree programs are available in clinical psychology, the American Psychological Association (APA) recognizes the doctorate as the minimum educational requirement for entry into professional practice as a psychologist (APA, 1987b, p. 3). Therefore, in this chapter, the stages toward the doctorate in clinical psychology and subsequent postdoctoral training and licensing will be discussed. A career as a clinical psychologist is rife with both tremendous challenges and unanticipated rewards. The road to becoming a clinical psychologist is a long one divided by several distinct stages that include college, graduate school, clinical internship, postdoctoral fellowship, licensure, and finally employment and advanced certification. In this chapter, each of these progressive stages will be reviewed. Although college students may not need details on postdoctoral training, licensing, employment, and board certification this early in their careers, this information is included in this chapter to provide a complete road map of the training process.
Fig. 6.3 The principal physical, chemical, and biological factors which govern the well-being of the macrofauna of the hyporheic zone. Groundwater upwelling primarily affects the temperature, dissolved oxygen content, and redox conditions, hence a shift in the relative proportions of downwelling and upwelling waters in the hyporheic zone can have major implications for the survival of macroinvertebrates, the viability of salmonid eggs buried in redds, etc. (Adapted after Boulton 2000.)
Account Titles Cash Credit card receivables Prepaid insurance Food inventory Beverage inventory Building Equipment Accounts payable Notes payable Gram Disk, capital Sales revenue Wages expense Salaries expense Utilities expense Miscellaneous expense Accounts Totals
Note. 1 means student provided data; 0 means student did not provide data. These six patterns are those involving the largest numbers of participants. Ten additional patterns, each involving fewer than 20 students, are not shown. The predictor variables gender and religiosity, which were formed by combining data from all ve waves, had so little missing data that they are not shown here.
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