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data distribution in network-intensive collaborative applications [19]. Domains that have benefited from Quanta include computational science and engineering, earth sciences, and bioinformatic sciences [6, 22 24]. Quanta emerged from nearly a decade s experience in connecting immersive CAVE systems [25] to each other and to supercomputers a concept called TeleImmersion [26]. CAVEs are 10 10 10 foot virtual reality rooms that create realistic 3D computer imagery through the use of rear-projected stereoscopic computer graphics. Quanta s predecessor, CAVERNsoft [26,27], has been widely used by the CAVE community to develop advanced tele-immersive applications. CAVERNsoft was unique in that it marked the first time a wide-area shared memory abstraction was used to synchronize data within a virtual reality application. CAVERNsoft was also one of the earliest examples of what is known today as peer-to-peer computing. Quanta inherits from CAVERNsoft all of the data-sharing services that have been found to be essential for developing network-intensive applications. Capabilities include UDP and TCP network reflectors (needed to support collaborative applications), persistent shared memory (to save the state of a collaboration), message passing and remote procedure calls, high-performance remote file I/O (able to handle both 32- and 64-bit files), a variety of transmission protocols including forward errorcorrected UDP (to provide low-latency, low-jitter streaming), parallel TCP, Reliable Blast UDP (RBUDP), and soon LambdaStream (a streaming high-throughput reliable protocol). The key to Quanta s success has been in providing advanced networking techniques in a way that is accessible to application developers who are not networking experts. Tangible tools provide a systematic means to deploy advanced capabilities to the audiences that most desperately need them but who do not have the expertise to interpret the complex network research literature.

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Empirical Loss Distributions The objective of the actuarial approach is to provide an estimate of the loss distribution associated with operational risk. The simplest way to accomplish that task is to collect data on losses and arrange the data in a histogram like the one illustrated in Exhibit 8A.2. Since individual nancial institutions have data on high-frequency, lowseverity losses (e.g., interest lost as a result of delayed settlements) but do not have many observations of their own on the low-frequency, highseverity losses (e.g., losses due to rogue traders), the histogram will likely be constructed using both internal data and (properly scaled) external data. In this process, individual institutions could bene t by pooling their individual observations to increase the size of the data set. Several industry initiatives are under way to facilitate such a data pooling exercise the Multinational Operational Risk Exchange (MORE) project of the Global Association of Risk Professionals (GARP) managed by NetRisk, a project at PricewaterhouseCoopers, and a BBA project. Explicit Distributions Parameterized Using Historical Data Even after making efforts to pool data, an empirical histogram will likely suffer from limited data points, especially in the tail of the distribution. A way of smoothing the histogram is to specify an explicit distributional form. However, a number of analysts have concluded that, rather than specifying a distributional form for the loss distribution itself, better results are obtained by specifying a distribution for the frequency of occurrence of losses and a different distribution for the severity of the losses.5 In the case of frequency, it appears that most analysts are using the Poisson distribution. In the case of severity, analysts are using a range of distributions, including a lognormal distribution and the Weibull distribution. Once the

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7 GSM#13 asked the PN to elaborate a system veri cation program, allowing continuous validation of the GSM speci cations. But WP2 commented at GSM#14 that this would mean a delay, as several administrations had already started validations. GSM#14 decided that each administration should conduct its own veri cations and that a coordinating committee should be established. Cf. also TDoc GSM 51/87, TDoc GSM 107/87, TDoc GSM 96/88, TDoc GSM 222/88 and GSM#21 Report, Section 8.

The application consists of one or more application components. Application components are clients for the transactional resources, or the programs with which the application developer implements business transactions. As you might have guessed, enterprise beans are the application components of an EJB-based transactional system. Application components operate on data by using the services of a resource manager.

GETTING T&E UNDER CONTROL T&E reimbursements, especially when employees are paying credit card bills out of their own pocket, can be a very touchy issue in accounts payable. It is even more delicate if the manager is new, the process is unruly, and the new manager wants to impose some discipline on the process. The problem is summarized below, as is the advice offered by two seasoned AP professionals who have dealt with similar circumstances themselves. Problem: A very large distributor s AP department is in chaos. Deadlines and guidelines for employees to submit their T&E expenses were never established. Thus, accounts payable rarely has a reasonable amount of time to audit the expenses, input into SAP, and download into the bank for payment, after which AP has to deal with the invariable kick-outs that occur due to bad bank information for individuals. The problem for this AP department is exacerbated because the company does not have a corporate card, so employees are paying out of pocket, and sometimes their bills are high. Accounts payable wants to be sensitive to the cash-flow issue. However, more than occasionally,

the US documents and keep within the guidelines of the ANSI process. After much discussion, the concept of using ETSI SMG documents as normative reference in the US standards documents was nally agreed. This allowed the maintenance and evolution to continue unimpeded without unnecessary duplication of resources and effort. In fact, this concept would form the basis of the SDO relationship to the 3GPP.

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