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Resource America went public in 1986 as a specialty nance company that bought commercial mortgages at a discount. It also held some energy assets like gas wells and pipelines. It built up Fidelity Leasing and in 2000 sold it to ABN Amro for $583 million, approximately twice the net assets of the lease portfolio, a signi cant premium. Later, REXI IPO d its energy assets by selling shares of Atlas America in 2004 and then spun off its remaining shares the next year. In 2005, REXI also created Resource Capital Corporation, a real estate investment trust (REIT) that trades separately under the ticker RSO. Overall, REXI has a very good track record of accumulating assets on the cheap and selling them at good prices, with solid gains for shareholders. Today, REXI manages assets across a broad range of categories and earns attractive spreads on structured nance pools. We believe that while some of these pools may experience problems, REXI has modest liability, which is more than discounted in the stock price. In addition to substantial excess assets outlined later, we estimate that REXI has earnings power of over $1 per share, though it will not reach this level in 2009; the company s guidance is $0.50 to $0.70 per share. REXI operates in three segments: nancial fund management (FFM), which manages various types of asset-backed securities; real estate,

Finally, we attempt to open the file with a call to CreateFile(), and report our success of failure to the user with MessageBox().

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You will declare an array, Customer_array, to store the customers names and a hash, Customer_hash, to store the customers names and their choices of books:

The algebraic decoders presented to this point in the book are bounded distance decoders, meaning they are capable of decoding up to to = [(dmin- 1 ) / 2 ] errors. In the remainder of this chapter we discuss a list decoding approachto Reed-Solomon (and related) codes which is capable of decoding beyond to errors. A list decoder generally returns several possible decoded messages. However, for many codes the size of the list is usually small, so that only one decoded message is usually returned. An extension of this decoding algorithm provides a means for algebraic soft decision decoding of Reed-Solomon codes. 7.6.1 Bounded Distance, ML, and List Decoding Consider an (n,k , d ) Reed-Solomon code C. Three different decoding paradigms can be employed in decoding such codes. In bounded distance (BD) decoding, the following problem is solved: For a distance e such that 2e 1 5 dmin, given a received vector r, find a codeword c E C which is within a Hamming distance e of r. There exist many efficient algorithms exist for solving this (all of the algorithms in chapter 6 are BD decoders), and for a t-error correcting code the answer is unique when t 2 e . However, if r lies at a distance greater than [(dmin- 1)/2] from any codeword, a decoding failure will result.

1.5.3 Trading Process Network:

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