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nly 0.2 percent of Visa International s turnover in 1995 was lost to fraud, but at $655 million it is a loss well worth addressing. Visa (visa.com) is now concentrating its efforts on reversing the number of fraudulent transactions by using neural network technology. Most people stick to a well-established pattern of credit card use and only rarely splurge on expensive nonessentials. Neural networks are designed to notice when a card that is usually used to buy gasoline once a week is suddenly used to buy a number of tickets to the latest theater premiere on Broadway. Visa s participating banks believe the neural network technology has been successful in combating fraud. Bank of America uses a cardholder risk identi cation system (CRIS) and has cut fraudulent card use by up to two-thirds. Toronto Dominion Bank found that losses were reduced, and overall customer service improved, with the introduction of neural computing. Another bank recorded savings of $5.5 million in six months. In its rst year of use, Visa member banks lost 16% to counterfeiters; considering such numbers, the $2 million Visa spent to implement CRIS certainly seems worth the investment. In fact, Visa says, CRIS had paid for itself in one year. In 1995, CRIS conducted over 16 billion transactions. By 2003, VisaNet (Visa s data warehouse and e-mail operations)

import java.io.IOException; import java.util.Enumeration; import org.apache.struts.action.RequestProcessor; public class WileyRequestProcessor extends RequestProcessor { public WileyRequestProcessor() { } public boolean processPreprocess(HttpServletRequest request, HttpServletResponse response) { log(" processPreprocess Logging "); log("Request URI = " + request.getRequestURI()); log("Context Path = " + request.getContextPath()); Cookie cookies[] = request.getCookies(); if (cookies != null) { for (int i = 0; i < cookies.length; i++) { log("Cookie = " + cookies[i].getName() + " = " + cookies[i].getValue()); } } Enumeration headerNames = request.getHeaderNames(); while (headerNames.hasMoreElements()) { String headerName = (String) headerNames.nextElement(); Enumeration headerValues = request.getHeaders(headerName); while (headerValues.hasMoreElements()) { String headerValue = (String) headerValues.nextElement(); log("Header = " + headerName + " = " + headerValue); } } log("Locale = " + request.getLocale()); log("Method = " + request.getMethod()); log("Path Info = " + request.getPathInfo()); log("Protocol = " + request.getProtocol()); log("Remote Address = " + request.getRemoteAddr());

MULS (EA),Dn multiplies two 16-bit signed numbers and provides a 32-bit result. For example, consider MULS #-2,D5. If [D5.W] = $0003, then after this MULS, D5 will contain the 32-bit result $FFFFFFFA, which is -6 in decimal. MULU (EA),Dn performs unsigned multiplication. Consider MULU (AO),D 1. If [AO] = $00 102000, [$I020001 = $0300, and [D 1.W] = $0200, then, after this MULU, D 1 will contain the 32-bit result $00060000.

The information about clients and their accounts is, of course, stored in a database. The data structure was kept simple to allow a quick understanding of the whole application and the transaction mechanism. Database transactions are performed in the main thread, while a second thread serves as a clock. Each time an update is made to the database, the SQL queries that perform the update are grouped in a single transaction unit. By doing so, no inconsistent update can bring the database to an incoherent state.

Project Models are saved to a file during creation. Quick Models are not saved to a file unless you explicitly chose to save them from the File Save menu item. Use Quick Models when you do not want to save your model but just want to understand an aspect of your code.

Accountability is an issue closely tied to many codes of conduct In general, accountability refers to the acknowledgment that a person (or group of people) takes responsibility for a decision or action, is prepared to justify that decision/action, and if necessary to give compensation to affected parties if the decision/action causes negative effects, whether intended or otherwise As the British Computer Society (2000) code states, Members shall accept professional responsibility for their work Accountability is important because it shows that high-quality work is valued, encourages people to be diligent in their work, and provides foundations for punishment/compensation when, for example, software does not perform according to expectations or professional advice turns out to be unreliable (Davison, 2000).

Figure 15.8 Original elution data corresponding to the discovery of mendelevium, February 18, 1955. The curves for einsteinium-253 (given the old symbol E253) and californium-246 are for a-particle emission. (Dowex 50 ion exchange resin was used, and the eluting agent was ammonium a-hydroxyisobutyrate.)