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Implicitly so far, we have been drawing defaults out of a single urn the average urn in Exhibit 4.19. In a Macro Factor Model, defaults depend on the level of economic activity, so we would draw defaults out of more than one urn. Exhibit 4.19 envisions three urns one for the average level of economic activity, another if the economy is in a contractionary state, and a third if the economy is in an expansionary state. Note that the probability of default the number of black balls in the urn changes as the state of the economy changes. (There are fewer black balls in the expansionary urn than in the contractionary urn.) Consequently, the way that a Macro Factor Model works is as follows: 1. Simulate the state of the economy. (Note that we are simulating a future state of the economy, not forecasting a future state.) 2. Adjust the default rate to the simulated state of the economy. (The probability of default is higher in contractionary states than in expansionary states.) 3. Assign a probability of default for each obligor, based on the simulated state of the economy.

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Figure 2-3 The electromagnetic spectrum. The figure shows a logarithmic distance scale (range, 1 mm to 0.1 nm). One side shows the wavelength ranges of common classes of electromagnetic radiation; for reference, the other side indicates the sizes of various cells and macromolecules. Thus, a red blood cell (7.5 m) is 15 times larger than a wavelength of visible green light (500 nm). The resolution limits of the eye, light microscope, and electron microscope are also indicated. For the eye, the resolution limit (0.1 mm) is taken as the smallest interval in an alternating pattern of black and white bars on a sheet of paper held 25 cm in front of the eye under conditions of bright illumination. Notice that the range of visible wavelengths spans just a small portion of the spectrum.

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Up to 500 Employees Across the board Total Percent of staff affected 1% 3% 4% 7% 8% 10% 10% or more Overall Areas affected Accounting/finance Production Other Corporate services (e.g., mailroom, customer service legal, etc.) lT Sales/marketing HR department 43.1% 14.6 8.5 10.8 10.0 52.3 25.4 30.8 25.4 23.8 20.8 22.3 15.4 More than 500 Employees 47.8% 17.4 7.2 10.1 13.0 53.6 36.2 24.6 24.6 26.1 27.5 23.2 26.1 2004 Overall 44.7% 15.6 8.0 10.6 11.1 52.8 29.1 28.6 25.1 24.6 23.1 22.6 19.1 2003 Overall 42.2% 25.0 25.0 18.8 31.3 44.0 24.8 22.9 11.9 19.3 17.4 14.7 9.2

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Means of estimating these characteristics need to be de ned Some commonly used estimators are: Mean Time Before Failure (MTBF) The average time between failures Mean Time to Provide Service (MTPS) The average time from nalizing agreement between the service operator and the customer to having the service in operational use This can be considered to be a formalization of the service implementation time mentioned above Mean Time to Restore Service (MTRS) Average time from reporting a fault to service being restored Failure is used in the above list generically to indicate a state of insuf cient service quality support in the network To de ne the abnormal conditions more precisely, the TeleManagement Forum (TMForum) de nes different levels of deviations from the normal operation of the service support in the network [SMH01] In what follows, the terms have been interpreted from a service quality support viewpoint.

Research in psychology reveals that when a person, especially a first-time offender, commits a crime, he or she becomes engulfed by emotions of fear and guilt. Those emotions cause the individual to experience a significant amount of stress, and in order to cope with stress, the individual will exhibit unusual and recognizable behavior patterns. Some recognizable behavior patterns are insomnia; increase in drug and alcohol abuse and smoking habits; unusual irritability and suspiciousness; inability to relax; lack of pleasure in things usually enjoyed; fear of getting caught; inability to look people in the eye; visible embarrassment around friends and others; defensiveness or argumentativeness; unusual belligerence in stating opinions; unsolicited confessions; obsessive contemplation of possible consequences; constant development of excuses and identification of scapegoats; tendency to work standing up; and increased perspiration. It is not any particular behavior, but rather changes in behavior that signals fraud. People who are normally nice may become intimidating and belligerent; people who are normally belligerent may suddenly become nice.22

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The following de nitions assume that the desired service quality support has already been de ned Anomaly is a discrepancy between the desired and actual performance Defect is a limited interruption in the capability of network element or network to perform required function Impairment is a condition giving rise to anomalies and defects without causing a failure Failure is the termination of the ability of a network element or network to provide the required function Fault is the inability of a network or network element to provide service quality support, excluding maintenance reasons, external causes, or planned actions Fault is often the result of a failure, but may also exist without a failure It is important to note the role of service de nition in fault management according to these de nitions.

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