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This program produces the same output as its preceding version. In this example, the function show_who( ) defines a reference parameter of type Base. Inside main( ), the function is called using objects of type Base, first_d, and second_d. Inside show_who( ), the specific version of who( ) that is called is determined by the type of object being referenced when the function is called. The key point to using virtual functions to achieve run-time polymorphism is that you must access those functions through the use of a base class pointer or reference. Although it is legal to call a virtual function just as you call any other normal function, by applying the dot operator to an object, it is only when a virtual function is called through a base class pointer (or reference) that run-time polymorphism is achieved. At first glance, the redefinition of a virtual function in a derived class looks like a special form of function overloading. But this is not the case, and the term overloading is not applied to virtual function redefinition because several differences exist. First, the prototypes for virtual functions must match. As you know, when overloading normal functions, the number and type of parameters must differ. However, when redefining a virtual function, these elements must be unchanged. If the prototypes of the functions differ, then the function is simply considered overloaded, and its virtual nature is lost. Also, if only the return types of the function differ, an error occurs. (Functions that differ only in their return types are inherently ambiguous.) Another restriction is that a virtual function must be a nonstatic member, not a friend, of the class for which it is defined. However, a virtual function can be a friend of another class. Also, destructor functions can be virtual, but constructors cannot. Because of the restrictions and differences between overloading normal functions and redefining virtual functions, the term overriding is used to describe the virtual function redefinition. Once a function is declared as virtual, it stays virtual no matter how many layers of derived classes it passes through. For example, if second_d is derived from first_d instead of Base, as shown in the following example, who( ) is still virtual, and the proper version is still correctly selected:
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// Demonstrate covariance and contravariance. using System; class X { public int Val; } // Y is derived from X. class Y : X { } // This delegate returns X and takes a Y argument. delegate X ChangeIt(Y obj); class CoContraVariance { // This method returns X and has an X parameter.
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This section will discuss some of the IGMP properties you can manage on your appliance s interfaces. Here are the commands you can configure for IGMP:
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The goal with a spear design is to maximize the impact when the weapon head hits the target. The force behind the weapon at the point of impact does not matter, because the effect on the target will be determined entirely by the kinetic energy of the spear at the moment of impact. The kinetic energy of the spear is proportional to its mass times the square of its velocity, so increasing the speed of the spear will do more to make it an effective weapon than increasing its mass. Excess force on the spear at the moment of impact will mainly have the effect of pushing the spear-armed bot and its target away from each other; the traction holding the bots in place on the floor is small compared to the forces required to punch through armor. Figure 10-15 shows such robots. Ideally, your spear bot should strike the opponent near the end of its travel for maximum effect. In practice, however, this will be difficult if not impossible to arrange. In most cases, the spear will strike the target robot after only a fraction of its travel. If possible, you should design your spear to accelerate as much as possible early in its travel. Most spear designs use a pneumatic cylinder to fire the weapon. With a pneumatic ram, the top speed of the weapon is limited by the rate of gas flow into the cylinder. All components on the gas flow path from the storage tank to the cylinder regulator, valves, tubing, and fittings should be made as large-bore (internal diameter) as possible for maximum flow rate.
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The yield contextual keyword is used with an iterator, which is a method, operator, or accessor that returns the members of a set of objects, one element at a time, in sequence. Iterators are most often used with collections.
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charge a battery at no more than this constant-current C/20 rate. To determine the first 20 percent charging current, Charging Current 5 Battery Capacity/Time C/20 For a 200 ampere-hour capacity battery, charging current would be Charging Current 200/20 5 10 amps In other words, you would limit this battery s initial charging current to 10 amps. You can blast your battery with 200 amps and charge it in 1 hour, but you will prematurely age and kill it it will not deliver its full, useful life to you. The graph at the lower left in Figure 9-3 shows the result of current-limited C/20 rate charging during the first 20 percent part of the charging cycle. The voltage rises gently and your battery is very happy. In the middle of the charging cycle, you can charge at up to the C/10 rate. This is the fastest rate that efficiently charges a lead-acid battery. This rate is not as efficient as the C/20 rate more energy is wasted in heat if you recall the I2R losses but it gets the charging job done faster. At even less efficiency (and more risk to your batteries), you can bump it up to higher C/5 or C/3 rates during this period of recharging if time is essential to you, and if you closely monitor the battery s temperature so its operating limits are not exceeded and you don t wind up cooking it. Charging current would be 20 amps at the C/10 rate for the 200 ampere-hour battery. Figure 9-3 shows that voltage, after a step increase when current settings were changed, rises slowly to its 90 percent state-of-charge value of approximately 2.50 volts.
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Listing 6-4 is fairly straightforward. The first ACL statement denies access to the segment. The second and third ACL statements allow all IP traffic from and to travel to this is denied by default because of the security levels of the two interfaces involved. The fourth, fifth, and sixth ACLs deny any traffic from the DMZ headed to the three internal subnets. This prevents other devices on the dmz interface from accessing resources on and also prevents any device on this segment from accessing the two networks on the internal router: and These statements are needed because of the statement that follows this (the seventh statement), which allows traffic from any device on to go anywhere you need to deny the specifics before you permit everything. The second to the last statement in the configuration drops all packets. I ve
port level of at least 10 dBmV at the 750-MHz frequency. Proper drop cable shielding effectiveness is also necessary to control signal leakage and ingress. You will often have several choices for branching within a service area design. If a manual design method is being used, the designer can ponder the various choices, taking signal level and cost factors into consideration. Signal splitters and directional couplers are the passive devices used for system street branching. Figures 2-8 and 2-9 illustrate two methods serving the same residential street layout. One method employs a balanced output splitter and the other one uses directional couplers. Figure 2-8, using two direction couplers, has two short branches with one four-port tap each and one long branch with two taps before a line extender is required. Figure 2-9, on the other hand, could use two taps in three directions, with the last tap a terminating tap before a line extender ampli er is required to extend the system. Computer-aided design and drafting programs keep a running tabulation of signal levels. When this level approaches a predetermined level,
Fraud management toolkit. The fraud management toolkit provides fraud investigators with a source of alerts of suspect calling patterns in real time, as well as a means of pulling these alerts into fraud investigation cases. The architecture of the toolkit is shown in Figure 33.16. CDRs from the real-time CDR generator are fed to a programmable detection and analysis engine, which matches calls against known suspicious calling patterns and generates fraud alerts when matches are detected. Fraud detection modules control the CDR builder and detection analysis engine to detect selected types of known fraudulent calling patterns and generate appropriate alerts. The alerts are supplied to a case manager, which gives each alert a severity weighting number and then attaches each alert to a case depending on some key such as the calling party number. Each case will have a severity weighting that is the sum of the
int twod[10][20];
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