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algorithm used will affect the resultant media bit-rate. Take video compression as an example. There are many video compression algorithms available, such as MPEG2, MPEG4, and H.264. In terms of compression ef ciency, i.e., achievable compression ratio at a given video quality level, it is generally agreed that MPEG2 < MPEG4 < H.264. However, the more ef cient video codec such as H.264 also demands substantially more computations in both the encoding and decoding processes. Thus, choosing a more ef cient compression algorithm such as H.264 will lower the network bandwidth required but will increase the computation complexity at both the encoder and decoder. Note that for stored media the encoder complexity is less of an issue as the encoding process can be performed of ine. However, if the media stream is encoded from a live source in realtime, then the encoding complexity will become a signi cant constraint. Decoding, on the other hand, is usually less complex than the encoder and thus presents less of an issue in the choice of codec in a media streaming system.



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14 Nov 2017 ... Normally, scanned documents are stored in the TIF or TIFF format on the ... Now, converting TIF to PDF files have always been a problem for the .... If you try to add more than one document in the software , it will save the PDF in individual file . ... How to Convert JPG to PDF for Free · Easily Edit Metadata or ...

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TIFF to PDF Converter is a simple, lightning-fast desktop utility program that lets you convert TIFF (photos, scans, drawings and faxes) into Acrobat PDF documents. You can merge several TIFF files into a single PDF file , or convert each TIFF file into a separate PDF file .

I must have let my eyes fall out of my head at that moment, because it was easily apparent that I had no idea what he was talking about So I acted like I hadn t heard him and stared out the window Busy day today on the trading floor, I told him I said this with a matterof-fact tone, as if I visited trading floors all the time and was pleased to see everyone busy at work Sure is CPI rocked the markets this morning Sent stocks way up in a hurry Stocks were irrelevant My buy trade on the GBP/USD was far more important And the dollar I asked He grinned So you re a student of the markets, I see I nodded I do a bit of trading myself Well, then, he said, You ll be happy if you re short dollars today.





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10 Oct 2009 ... TIFF To PDF Converter Software offers a solution for users who want to convert one or more TIFF image files into PDF format. The user chooses ...

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This free online TIFF to PDF converter allows to combine multiple images into a single PDF document. Besides TIFF, this tool supports conversion of JPG, BMP, ...

Within the service class the non-functional properties and imported ontologies attributes play a role that is similar to that found in the ontology class with the minor addition of a quality of service nonfunctional property. An extra type of mediator (WW Mediator) is also included, in order to deal with protocol and process-related mismatches between Web services. The nal two attributes de ne the two core WSMO notions for semantically describing Web services: a capability which is a functional description of a Web Service, describing constraints on the input and output of a service through the notions of preconditions, assumptions, postconditions, and effects; and Web service interfaces which specify how the service behaves in order to achieve its functionality. A service

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In baseline rebuild, the transfer capacity of the spare server can become the bottleneck even if the remaining servers have abundant idle capacities available An alternative approach is to rebuild the unavailable data units before transferring them to the spare server In this way, only the rebuilt data are sent to the spare server and hence the limited transfer capacity of the spare server can be better utilized To achieve this, we can employ a distributed rebuild scheme to distribute the rebuild computations over all the remaining servers We rst divide the unavailable data into (N S 1) equalsize subsets, with each subset then rebuilt by one of the remaining (N S 1) servers, as shown in Figure 146.

We have presented several techniques from Knowledge Discovery that are useful for semi-automatic ontology construction In that light, we propose to decompose the semi-automatic ontology construction process into several phases ranging from domain and data understanding through task de nition via ontology learning to ontology evaluation and re nement A large part of this chapter is dedicated to ontology learning Several scenarios are identi ed in the ontology learning phase depending on different assumptions regarding the provided input data and the expected output: inducing concepts, inducing relations, ontology population, ontology construction, and ontology updating/extension Different groups of Knowledge Discovery techniques are brie y described including unsupervised learning, semi-supervised, supervised and active learning, on-line learning and web-mining, focused crawling, data visualization In addition to providing brief description of these techniques, we also relate them to different ontology learning scenarios that we identi ed.

The server responsible for a subset will receive the required data/redundant units from the other (N S 2) servers, rebuild the unavailable units, and then send the rebuilt units to the spare server for storage To derive the rebuild rate of the distributed rebuild algorithm, we rst note that the sum of transfer rates in and out of the remaining (N S 1) servers is equal to SS (1 )(N S 1) Second, to rebuild each data unit we need 2(N S 2) transfers (half for transmission and the other half for reception) of data/redundant units from the other (N S 2) servers to the rebuild server the server responsible for rebuilding the unavailable data unit.

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