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The precise frequency to be operated in a given country or region will be chosen in the above quoted bands according to ITU Radio Regulations and allocations2 and to local regulations and allocations. Full protection of other services, and, in particular, of the GSO satellite services is ensured as follows (see also above in AP6.1-2.2). When a SkyBridge satellite with a spot-beam on a given gateway cell enters the cell non-operating zone (i.e. within a 10 zone around the GSO, when an interference condition potentially exists), the spot-beam is shut down and the traffic is handed over to another satellite in the constellation not then in the non-operating zone for this cell. The implementation of this interference avoiding by proper frequency sharing is managed by the MMC. Moreover, severe conditions are imposed to the SkyBridge emissions (power flux-density limitations, out-of-band emissions, etc.) in order to protect other services and, in particular, terrestrial communication services.

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A target or projected return for the portfolio. The return earned by funds with a similar purpose and strategy. The market return for the asset class, as represented by a market

Grasping the Basic Terminology One-way encryption versus two-way encryption Algorithms Shared-key cryptography Public-key cryptography Digital certificates Protocols Reviewing the Java Cryptography Package Writing a Java Program Using JCE Magazine Publisher Business Case Airline Reservations Business Case Summary 410 410 412 415 416 417 417 420 421 422 424 426.

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Encryption is the process of converting readable and recognizable data into unreadable data in order to conceal the information from everyone except those who have the key to decrypt it to its original state. The encryption process requires a key to ensure that the process is consistent and the encrypted data can be decrypted. Early civilizations such as the Egyptians, Assyrians, Chinese, Greeks, Romans, Arabs and others have used encryption to protect trade secrets, government communications, military plans and other sensitive information. Today, the need to encrypt data and conceal sensitive information is more prevalent and accessible through the use of computers that can provide sophisticated encryption/decryption algorithms. In its most basic mathematical form, a string of data is subjected to an arithmetic operation against a key to produce an encrypted string. The encrypted string and the key hold the information which can be reversed to its original state by applying the reverse of the initial operation. In other words, if we wanted to encrypt the word Hello , we would read the string character by character: H, e, l, l and o. If we take the ASCII value of each of these characters (72, 101, 108, 108 and 111) and add a constant such as 7 to each one of these ASCII values, we obtain the following: 79, 108, 115, 115 and 118. By converting these ASCII values to their character equivalent, we obtain the following string: Olssv. In this case, the encrypted word is Olssv and the encryption key is the number 7.

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n the previous chapter, we examined various models to describe volatility structures. In this chapter, we examine another way to model volatility namely using statistical models. Statistical models, such as generalized autoregressive conditional heteroskedasticity (GARCH), provide the advantage over parametric approaches in that they use robust statistical methods to actually estimate volatility structures. We examine several of these models and show how they can be used for volatility estimation and forecasting. In section 8.1, we give an overview of statistical models and why they are needed. In section 8.2, we discuss moving average models and provide an implementation. In section 8.3, we discuss exponential moving average models and provide an implementation. In section 8.4, we discuss GARCH models. In section 8.5, we discuss asymmetric GARCH models. In section 8.6, GARCH models for high-frequency data are examined. In section 8.7, estimation problems of GARCH models are discussed. In section 8.8, we discuss using GARCH in an option pricing model using a lattice. Finally, in section 8.9, we discuss GARCH forecasting and provide a GARCH forecasting example.

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