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Recommendation ITU-R F.1094 recommends a performance degradation criterion of 10% for services shared on a co-primary basis, and Recommendation ITU-R SF.357 specifies interference criteria into terrestrial radio-relay links. Recommendation ITU-R SF.1005 recommends that for shared bands allocated in both directions to the GSO FSS, the pertinent interference criterion (long term and short term) from earth stations operating in RBW to stations in the FS should be lower by the following values than those calculated by the methods described in Recommendations ITU-R IS.847 and SF.1006: 7 dB in the band 10-15.4 GHz, 5 dB in the band 15.4-20 GHz and 3 dB above 20 GHz. Recommendation ITU-R SF.1005 pertains to frequency bands above 10 GHz due to the fact that most bands below 10 GHz are heavily used by the FS and then RBW mode is not feasible in these bands. It is recognized that similar concepts would be applicable to non-GSO FSS and that some tightening of the FDP criterion of 10% would be required when considering interference from RBW non-GSO MSS FL. iv) Feasibility of sharing: pfd limits of Recommendation ITU-R SF.358

As explained above, digital television gives an improved picture quality, although this quality depends, of course, on the compression factor. The picture improvement in quality and clarity results from the fact that compression technologies remove the distortions which cause blurring or ghosting in conventional analogue transmission. As concerns the quality of the satellite link proper, provision is generally made in the satellite link budget to guarantee a very good transmission quality, even in poor meteorological conditions and with small TVRO antenna dishes. This is because, due to the implementation of powerful error correcting codes (e.g. Reed-Solomon codes), the system performance objective is "quasi error free"

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POST /GetBookPrice HTTP/1.1 User Agent: Mozilla/4.0 (Linux) Host: nramesh:8080 Content-Type: text/xml; charset= utf-8 Content-length: 546 SOAPAction: /GetBookPrice < xml version= 1.0 > <SOAP-ENV:Envelope SOAP-ENV:encodingStyle= http://schemas.xmlsoap.org/soap/encoding/ xmlns:SOAP-ENC= http://schemas.xmlsoap.org/soap/encoding/ xmlns:SOAP-ENV= http://schemas.xmlsoap.org/soap/envelope/ xmlns:xsd= http://www.w3.org/2001/XMLSchema xmlns:xsi= http://www.w3.org/2001/XMLSchema-instance > <SOAP-ENV:Body> <m:getBookPrice xmlns:m= http://jws.wiley.com/ > <bookname xsi:type= xsd:string > Developing Java Web Services</bookname> </m:getBookPrice> </SOAP-ENV:Body> </SOAP-ENV:Envelope>

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Once we develop a Web service, we create its WSDL definition. We can create this definition either manually or by using a tool. Many tools are available for generating a WSDL definition from existing Java classes, J2EE components (such as Servlets/EJBs), or from scratch. Once the WSDL definition is created, a link to it is published in a Web services registry (based on UDDI, for instance), so that the potential user(s) of this Web service can follow this link and find out the location of the Web service, the function calls that it supports, and how to invoke these calls. Finally, the user(s) would use this information to formulate a SOAP request or any other type of request based on the binding protocol supported, in order to invoke the function on a Web service.

The dirname() Method. You can use the os.path.dirname() method to retrieve the directory name from a path name. For example, the following code returns the directory name of the path /home/user1/file1 :

parser.parse( PurchaseOrder.xml , handler);

geometric basis onto which a geometrically invariant description of all segments is done, with respect to a given transformation class (e.g., similarities). This description can therefore be matched to a similarity-invariant description on the image side, provided by a corresponding group of detected segments. For this purpose, in the off-line phase a hash table for the object shape is built, consisting of an entry for each possible model basis, used to describe all the other segments. In the online recognition phase, randomly selected segments on the image provide a basis for describing all the other segments, so that each can vote for one or more matching segments in the hash table, and thus for the related basis. If a given model basis receives a large number of votes, there is evidence for the presence of an object instance, to which the matching segments must belong. This also provides a geometric transformation between model and image bases, so that the localization problem is also solved. We consider rst the case of two-dimensional similarities, and later, an extension of the three-dimensional case. For two-dimensional similarities, with roto-translation and uniform scale, it is possible to describe model segments in an invariant manner, by selecting

Klystrons are essentially narrow passband devices: about 40 MHz for 6 GHz klystrons, and 80 MHz for 14 GHz klystrons and sometimes more. These bandwidths suffice for traditional frequency

respectively. Notice that this is just the CRR binomial model. If < 1, then the middle probability is negative since 1 1/ 2 < 0, and the numerical procedure is unstable. Thus, the stretch parameter should always be greater than 1 to ensure positive probabilities and numerical stability. The binomial model is right on the edge of numerical stability with = 1.

Thus, as mentioned, a cap can be regarded as a portfolio of put options. Interest rate oors, in contrast to caps, protect holders from drops in oating rates by placing a lower limit on the interest rate charged on a loan. Thus, the payoff in a oor is: Nmax(R R(ti 1, ti), 0) To purchase a cap, a borrower needs to pay the premium for the cap. To reduce the premium, the borrower can sell a oor. This is analogous to selling an out-ofthe-money (OTM) put to pay for an OTM protective call that protects a short position in the underlying asset. The individual payments between [ti 1, ti] are called

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