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showed that expert athletes accumulated hours of sport-specific training similar to that of nonexperts until approximately 10 years of involvement in their sport (around age 15, or the beginning of the investment years) After age 15, the rate of sport-specific practice accumulation by experts escalated dramatically beyond that accumulated by nonexperts Consistent with Van Rossum s (2000) data with Belgium field hockey players, Baker et al also found that the number of hours of reported sport-specific training by expert athletes (4,000 hours, on average) was far short of the 10,000 hours of deliberate practice reported for expert musicians by Ericsson et al (1993) Baker et al also indicated that participation in other sports (eg, sports where dynamic decision making is necessary) during early phases of development may have augmented the physical and cognitive skills necessary for the athletes primary sport.

subsequently had Pussin transferred to the Salp tri re to help him reorganize the hospital. In Italy, Vincenzo Chiarugi (1759 1820), superintendent of the hospital of Bonifazio published his three volumes, On Insanity and its Classi cation (1793/1987). He issued hospital regulations in which he stated that mental patients should be given humanitarian care, restraint should be kept to a minimum, physicians should visit the wards daily, and a program of recreation and work should be initiated. He attributed insanity to congenital factors and to environmental in uences. John Conolly (1794 1866), a British physician, practiced enlightened treatment methods for the mentally ill, including minimal use of restraints when he became resident physician at the Hanwell Asylum in 1839 (Scull, 1985).

The same Australian athletes were asked in a follow-up study to rate their training activities on a scale from 0 (no help) to 3 (very helpful) with respect to perceived useful-.

Figure 2-3

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X m) matrix A is a resultant matrix if det{ A) is a resultant. (See Section 11.1.1 for the definit.ion of a resultant.)

customers must implement services like CALEA, routing of 911 calls to the PSAPs with callers identi cation and location information, and so on However, the enterprises may need to implement these services as well once they become fully dependant on IP-based telecommunication services Since the IP networks operate using shared resources in a distributed fashion, it is sometimes di cult to detect the identities and locations of the communicating parties in a VoIP session However, many distributed server, wiring diagram, and media access control (MAC address) level ltering mechanisms are currently being explored to resolve these issues Cost-E ective Implementation Delivery of voice and data services over multiservice IP networks will not be widespread until and unless the implementation of highly available and reliable VoIP service becomes economically feasible.

You can get the software development kit (SDK) at www.javasoft.com. It has all the libraries, instructions, and Java tools that work on the command line. The JavaSoft site is the place to go for information about writing Java and adding Java applets to your pages.

This Subsection de nes a taxonomy for localization algorithms based on their computational organization Centralized algorithms (Section 94) are designed to run on a central machine with plenty of computational power Sensor nodes gather environmental data and pass them back to a base station for analysis, after which the computed positions are transported back into the network Centralized algorithms circumvent the problem of nodes computational limitations by accepting the communication cost of moving data back to the base station This trade-off becomes less palatable as the network grows larger, however, since it unduly stresses nodes near the base station Furthermore, it requires that an intelligent base station be deployed with the nodes, which may not always be possible This scaling problem can be partially alleviated by deploying multiple base stations (forming a multitier network).

In contrast, distributed algorithms are designed to run in the network, using massive parallelism and internode communication to compensate for the lack of centralized computing power Often distributed algorithms use a subset of the data to solve for each position independently, yielding an approximation of a corresponding centralized algorithm where all the data are considered and used to solve for all the positions simultaneously There are two important approaches to distributed localization The rst group, beacon-based distributed algorithms (Section 95), typically starts with some group of beacons (Subsection 921) Nodes in the network obtain a distance measurement to a few beacons, then use these measurements to determine their own location In some algorithms, these newly localized nodes become beacons to help other nodes localize The second group approaches localization by trying to optimize a global metric over the network in a distributed fashion.