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In fact, the data model of ACeDB can be considered as the one of the first semistructured data models [McHugh 1997], Databases are also used for learning from biological sequences This is close to the problem of data mining; in other words, the extraction of knowledge from a large set of real-world data with machine learning techniques But in this case the schema of the database usually can be chosen according to the problem that has to be solved C Sander and R Schneider conceived HSSP [Sander 1991] as a data bank of aligned sequences The sequences are aligned using information on their two-dimensional and three-dimensional structures T Blundel [Blundel 1987]; [Blundel 1988] built a relational database for protein modeling including crystallographic information Part of the content of the database is computed to speed up the access GJL.

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Our previous discussion introduced the System Operations Model as the foundation for identifying, organizing, and conceptualizing the capabilities of the SYSTEM OF INTEREST (SOI) The results of this exercise can be translated into System Performance Speci cation (SPS) by the Acquirer or employed by a System Developer to analyze the SPS Referral For more information about analyzing speci cations, refer to the discussion on Speci cation Analysis practices in 28 Once the SOI s capabilities are identi ed, the key question is: WHO is accountable for performing those capabilities and achieving the associated level of performance More speci cally, are they performed by the MISSION SYSTEM or SUPPORT SYSTEM or both Once we understand HOW the MISSION SYSTEM and SUPPORT SYSTEM interact, we can allocate the interactions as constraints down to each entity s system elements (PERSONNEL, EQUIPMENT, etc).

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Ultimately system element interactions will be owed down as constraints to the EQUIPMENT and its supporting HARDWARE and SOFTWARE elements This section explores the MISSION SYSTEM and SUPPORT SYSTEM interactions Our discussions employ a matrix mapping technique to illustrate how system operations within the system Concept of Operations (ConOps) are allocated to pre-mission, mission, and postmission phases Since MISSION SYSTEM and SUPPORT SYSTEM operations are application dependent, we introduce a method for modeling the operations The discussion employs several examples to illustrate application of the method Author s Note 201 The discussions in this chapter establish a base for understanding how the system will be applied to perform missions and interactions You will nd people who believe this is a case of analysis paralysis Granted, you have to strike a BALANCE between LEAF level analysis details and being able to see the forest.

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Kemp [Kemp 1991] used an OODBMS (P/FDM, an extension of the functional data model) to store information about protein structures The Daplex language is used for definition and for querying the database The underlying system is written in Prolog; this allows complex queries that cannot be expressed directly in Daplex to be written in Prolog This review shows that biological databases need to store a static kind of information on sequences and also on dynamic information that is computed from the static one This computed information is used to detect patterns (intron-exon junctions [Dunham 1994]) and structural patterns in proteins [Kemp 1991], and to speed up or facilitate queries Our database stores computed information in two forms: function result and query result The originality of our work is in the management of dynamic knowledge..

Those who diminish the value of de ning system interactions are also the ones who: 1 Carry the information around in their heads 2 Fail to document anything..

System Analysis, Design, and Development, by Charles S. Wasson Copyright 2006 by John Wiley & Sons, Inc.

efforts, with the end goal of providing the customer with increased choice, reduced cost, and improved interoperability. This chapter reviewed some of the work being done in the industry to advance the uses and overall adoption of blade systems. It completes Part II of this book. Part III, Hardware, Facilities, and Software Considerations, moves on to discuss hardware, software, and data-center facilities considerations, both for choosing products and for planning and implementing those products.

3. Do not communicate their understanding to others. 4. Complain that everyone else should know what they know about the system. Remember, as an SE, one of your many roles is simpli cation that leads to decision making and immediate communications about those decisions. Complex system designs are simpli ed by decomposition and analysis; documentation is the preferred method for capturing engineering decision making for communications.

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