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Speaker recognition provides a convenient interface for authentication and identification applications. Most verification applications are text dependent, requiring the user first to enter a user ID by keyboard entry or swipe of a smart card, and then to repeat a predetermined word or short phrase. The user s voice sample is filtered and compared against the previously enrolled voice properties associated with their user ID. To prevent playback attacks, some applications randomly construct a pass phrase for the user to repeat from a small vocabulary of enrolled words and digits. The additional challenge and response thwarts or deters most casual imposters and presents a few more obstacles for the skilled and determined ones. However, overall voice verification is not regarded as one of the most accurate biometric technologies. Performance for text-dependent matching as described is generally expected to have a crossover error rate of about 2 percent, making it (by itself) only a reasonable solution for low-assurance environments. Also, speaker recognition performance is very susceptible to differences in the environment, and some conditioning and training is often necessary. For example, using different handsets or microphones between enrollment and verification will degrade performance, often in unknown and unpredictable ways. Additionally, speaker recognition performance is adversely affected if there are multiple speakers, if there is noise in the environment, or if the technology is used over degraded communication channels. Text-dependent verification performance can be tuned to work quite well in relatively clean, quiet environments, but the technology by itself does not constitute strong authentication. If voice verification is used in conjunction with a four-digit PIN, a 1 in 100 false acceptance rate (FAR) becomes roughly strengthened to 1 in 1,000,000. A more challenging (and less accurate) family of voice identification applications seeks to identify speakers though conversational, text-independent speech. These applications are used to analyze voice communications and also can be used to help scan or search communication channels. For example, banking and accounting businesses may desire a voice check as an additional security measure
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13.5.5 Development of an Optimality Criterion-2: Cam Criterion General. The optimality criteria derived up to this point are for output characteristics. It is also desirable to introduce criteria for cam contact stress to allow a compromise between output performance and cam contact stress. Contact Stress at Cam-Follower Interface. The Hertzian contact stress at the cam-follower interface is a nonlinear function of parameters such as pressure angles, cam offset, roller-follower mass, preload, follower-guide dimensions, follower-guide friction, and cam curvature. These parameters can be grouped into three nonlinear factors, each highlighting certain aspects of the cam contact stress. Factor SF allows for follower guide friction and follower pressure angle. It relates the follower-spring force ff on the output mass to the cam contact force fc and is given in normalized form as: Fc = Ff SF . (13.36)
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Here is how the program works. The constructor sets the instance variable x to a known value. In this example, x is used as an object ID. The destructor displays the value of x when an object is recycled. Of special interest is Generator( ). This method creates and then promptly destroys a Destruct object. The DestructDemo class creates an initial Destruct object called ob. Then using ob, it creates 100,000 objects by calling Generator( ) on ob. This has the net effect of creating and destroying 100,000 objects. At various points in the middle of this process, garbage collection will take place. Precisely how often or when is dependent upon several factors, such as the initial amount of free memory, the operating system, and so on. However, at some point, you will start to see the messages generated by the destructor. If you don t see the messages prior to program termination (that is, before you see the Done message), try increasing the number of objects being generated by upping the count in the for loop. One important point: The call to WriteLine( ) inside ~Destruct( ) is purely for the sake of illustration in this rather contrived example. Normally, a destructor should act only on the instance variables defined by its class. Because of the nondeterministic way in which destructors are called, they should not be used to perform actions that must occur at a specific point in your program. One other point: It is possible to request garbage collection. This is described in Part II, when C# s class library is discussed. However, manually initiating garbage collection is not recommended for most circumstances, because it can lead to inefficiencies. Also, because of the way the garbage collector works, even if you explicitly request garbage collection, there is no way to know precisely when a specific object will be recycled.
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The Standard Template Library and the string Class
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The requirements in this area will depend on the intended application of the tester. For testing telecommunications equipment and systems, the main requirement is standard coded data interfaces. (Clock signals generally are not required.) For each of the standard telecommunications bit rates, the interface should conform to a recognized telecommunications standard such as ITU-T G.703, ANSI TI.403, or ANSI TI.102/TI.105. The error detector also may have high-impedance inputs to allow bridging measurements, and the available sensitivity of the input should be able to handle levels of 20 to 30 dB below standard to cope with protected test points on equipment. For example, the input sensitivity might be quoted as +6 to 30 dBdsx, where dsx stands for digital crossconnect (the usual test reference point in a telephone exchange or central office). Unless specified otherwise, one can assume that the tester meets the standard jitter specifications at the interface (ITU-T Recommendations G.823, G.824, and G.825), since this is included in G.703. For general applications, more flexible and detailed specifications are needed. In most applications, both data and clock will be required as generator and error detector.
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While Bitmap is selected and a bitmap file has been specified, the Source and Bitmap Size options in the dialog become available. The Source option lets you link to and embed the bitmap with your document, but it has no bearing on how exported web pages are created. The Bitmap Size options let you to use either Default Size (the inherent size of the original bitmap) or a Custom Size as the size. By default, the Print And Export Background option is selected, which should remain so to be included as one of your web page elements.
As discussed in the Process section above, any given element will progress through several levels of detail, and it may be broken down into an increasing number of line items. For example, the rebar in a pad footing progresses as follows: Conceptual. At this level, the footing is not actually modeled. Its cost is derived from a dollars per square foot entry in the database linked to a zone in the model defining the footprint. The rebar cost is embedded in that number. Schematic/design development. Here the footing itself is modeled as a simple block, whose dimensions are refined as the design progresses. The concrete quantity is determined from the volume of the block, and the rebar quantity is now broken out as a separate line item defined as a number of pounds of rebar per cubic yard of concrete. This is the highest level to which we ll take concrete elements in an estimating model. Shop drawing. At this level, the rebar itself is modeled, and the quantity of various bar sizes is extracted from the model. It is usually only specialty subcontractors that find this level useful. Model Progression Specification Since various elements can progress to different levels of detail at different points in the design process, keeping track of what information is extractable from the model in what form and at what precision can become extremely confusing. Graphisoft developed an approach they call the Model Progression Specification (MPS) that we ve found very useful. See Fig. 5.5.6. Assemblies can have up to six levels of detail, from conceptual to shop drawing. Each level for each element in the model is specified in the MPS, and then these levels are mapped against the design phases to give a complete picture of the precision of the model at any point in the process. We are currently working with Graphisoft to develop our own MPS, but in the future the MPS will likely become a published standard. Figure 5.5.6 Model progression specification by Graphisoft. LoD means level of detail and refers to the detail in the model components. (Image courtesy of Webcor Builders.)
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