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where t1 , , t14 are the observed waiting times for the transition 3 4 and t15 , t20 are the observed waiting times for the transition 3 5 Note that the waiting times for transitions 2 3 and 4 5 are constant Figures 718, 719, and 720 show the Bayes predictive density, survivor, and hazard functions for this project The predictive mean is 3229 days and the standard deviation is 14191 days, so we do not expect to remain on schedule The large standard deviation is re ective of the very heavy tailed distribution for the 3 5 transition and the fact that once the project falls behind schedule it takes much longer to complete due to compounding problems The hazard increases steadily until about 30 days and then drops off.

simplify the pay process and ultimately save money, as attested to by a number of HR professionals. We are currently in the process of implementing a career banding structure that will streamline costs throughout base, bonus, and long-term pay, said the compensation consultant at a 10,000-employee manufacturing firm in the Northeast. Pay Cuts Relatively few companies decided to cut salaries, making this strategy last on the list for ways to curtail compensation costs. Only business services and manufacturing reported reducing salaries. Several companies reduced pay levels only temporarily one cited six months, for example. Other companies required employees to take unpaid time off. We had two weeks off without pay for all staff at company headquarters. The weeks were at the employees choosing. We saved $600,000, said the HR manager at a 100-person manufacturing firm in the South.

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This is re ective of the fact that project delays make it hard to complete in the 20 additional days shown in the gure However, once the problems are resolved, the hazard for the completion time will start to increase again in the future The 25th, 50th, 75th, 90th, 95th, and 99th percentiles are 2099, 2728, 3425, 4457, 5533, and 10376 days, respectively Any other desired quantity is also obtained easily from the predictive density Analysis from the owgraph model gives an entire waiting time distribution as well as the system reliability (survivor) and hazard functions for any total or partial waiting time For decision making, this immediately provides the mean, median, or any percentile of the waiting time distribution for a variety of input distributions.

Masquerading is a method of attack where the attacker obtains the identity of a different, usually an authorized, user. Masquerading is also sometimes referred to as spoofing. The attacker can then use the access rights and privileges of that user to perform malicious actions. Identity in centralized systems is usually validated at session startup time. In distributed object systems, however, the identity has to be passed and validated with each object request. The operations to credit and debit accounts in our banking example should obviously only be executed by authorized personnel of the bank in such a way that there is never a credit without a debit operation. A secure implementation of the banking example would have to distinguish different groups of users and grant the right to execute the c r e d i t and d e b i t operations only to a particular group. An attacker wishing to credit monies on his account would then have to use masquerading to obtain the identity of one of the authorized users.

The analysis from the current month along with prior information about potential delays gives a predictive distribution for the next month This gives the project team a gure for how many days behind schedule they are likely to be for the.

cryptanalysis The passive attack is therefore not considered feasible in any realistic time frame However, there are active attacks that can be used to obtain these pairs The quickest would be to steal the user s phone, remove the SIM and connect it to a phone emulator As the commands to the SIM are not authenticated in any way and the SIM does not have any knowledge of call protocols, and merely responds to a RAND and a request for the SRES, the emulator can be used to send 160 000 chosen RANDs to the SIM and receive the SRESs SIMs tend to have relatively slow clock speeds and it can therefore take up to 10 hours to obtain the pairs.

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