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The phenomenon of magnetism was known by the ancient Greeks when they discovered a type of iron ore called magnetite. Moorish navigators used a needle-shaped piece of this ore as the basis of a crude compass. It was found that when this needle-shaped piece of magnetite was suspended and allowed to move freely, it would always turn to the north. What we are dealing with here are permanent magnets. Remember, we used permanent magnets in the telephone subset to set up a magnetic eld in its earpiece (Section 5.3.2). Figure A.9 shows an artist s rendition of the magnetic eld around a bar magnet, the most common form of permanent magnet. In the early nineteenth century it was learned that this magnetic property can be arti cially induced to a family of iron-related metals by means of an electric current. The magnetic eld was maintained while current is owing; it collapsed when the current stopped. Magnets, as we know them today, are classed as either permanent magnets or electromagnets. A typical permanent magnet is a hard steel bar that has been magnetized. It can be magnetized by placing the bar in a magnetic eld; the more intense the eld, the more intense is the induced magnetism in the steel bar. The in uence of a magnetic eld can be detected in various ways, such as by a conventional compass or iron lings on paper where the magnet is placed below the paper.

input. The input of the controller is the difference between the actual sample and the interpolated value. If the interpolation is smaller than the sample, its slope is increased, otherwise it is decreased. The main advantage of the PLL-based approach is that it requires far less memory than the linear-regression technique (in essence only the current state of the integrator sum). The main disadvantage is that PLLs require a long convergence time to achieve a stable rate [17]. The NTP algorithm uses a PLL [18]. 7.4.4 Combining Multiple Time Intervals

and therefore F (x) l(x) lies within the step corresponding to x. Thus, l(x) bits suf ce to describe x.

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disease (COPD), the results are relevant because inhaled medications are a cornerstone of COPD treatment, as they are for asthma. It appears, then, that the presence of an intimate partner and satisfaction with close relationships may be associated with more appropriate medication utilization (more adherent use of medications; less necessity for oral steroids suggesting better disease control through inhaled medications), perhaps resulting in less morbidity due to asthma. As mentioned, patients with a tendency toward generalized fearful, catastrophizing reactions have more medical utilization. How might fearful reactions and social relationships interact in patients with asthma Two models are relevant: rst, the concept of the safety signal, which was developed based on persons with panic disorder. Safety signals are items (e.g., medications) or people associated with feelings of security and relief (Rachman, 1984). Among patients with asthma, the presence of the signi cant other may be hypothesized to decrease fearful cognitions, and be associated with lesser reports of asthma symptoms. An alternate hypothesis comes from kindling-sensitization models that posit that over time, increasingly lower levels of stimuli are needed to prompt the occurrence of the target symptoms (Post, Rubinow, & Ballenger, 1986). Extending this model to asthma, to the extent that the signi cant other is a source of stress, the signi cant other may be associated with increasing discomfort and greater reports of asthma symptoms over time. Theory-driven examinations of the role of the signi cant other and the moderating effects of relationship satisfaction await future research efforts.

vital area to manage a workforce that can deliver hospitality on a daily basis. Ensuring that an employee can conduct business without constant approval from a supervisor is the goal of empowerment. The mastery of empowerment requires a supervisor to train employees and to practice much patience. Employees who have been accustomed to direct supervision on all matters will not readily adapt to a work environment that requires independent thinking to solve challenges.

420 A P P L I C A T I O N S O F E V O L V I N G I N T E L L I G E N T S Y S T E M S T O O I L A N D G A S I N D U S T R Y

The error polynomial is thus obtained, and is then added to the received polynomial r (X ) to perform error correction. Example 5.10: Decoding for the concatenation of the RS codes CRS (28, 24) and CRS (32, 28) of a code vector of 32 bytes. The received vector contains two errors at positions 8 and 16. In the particular example, errors are erasures of the elements at those positions, represented in the received vector with the symbol 0 . The received vector r is the code vector calculated in Example 5.9 that when affected by the above error pattern becomes r = ( 100 90 80 70 0 0 0 70 60 50 200 100 89 139 249 0

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