The report will demonstrate how to implement a basic linked-list data structure in RAM for C. STRING. The result of this implementation is Memory Allocation or Data Management which obtains or releases memory space as required in C. STRING. The basic concepts of data structures such as strings, lists and stacks are discussed and the algorithm for allocation of space is developed. The C. STRING user language TOSCL, and the TOSCL parse algorithm with Data Management is described. Finally, the INTEL's Schottky Bipolar LSI microprocessor is microcoded to implement Data Management.

An interactive information system has been developed for the Computer Engineering Department to promote faster and more accurate means of obtaining academic information on a student or a group of students. It was also developed to provide departmental administrative personnel with information to guide course scheduling. The system has the capability of providing the following information concerning undergraduate students enrolled in the Computer Engineering program of the College of Engineering, University of Central Florida. 1. Basic information about the student, such as, address, telephone number, classification, etc. 2. A student's completed and in-progress courses 3. The grade and other information, such as, equivalent transfer credits or UCD resident credits for each course 4. Name and social security number of all the students working under the same advisor 5. Name and social security number of all the students in the same year of college (classification) 6. Name and social security number of all students that have taken or are taking a certain course 7. Name and number of all students with the same classification taking the same course The system provides the user with the additional capabilities to: 1. Update the information in the student's record by interactive operation 2. Delete a student from the data base 3. Print the sorted name and social security numbers of all the students that have a record in the data base

It has long been recognized that computer systems containing large data bases expend an inordinate amount of time managing the resources (viz. central processing time, memory, ... etc.) rather than performing useful computation in response to user I s query. This is due to the adaptation of the classical machine architecture, the so called von Neumann architecture, to a problem domain that needs radically different machine architecture for an efficient solution. The characteristics that distinguish the computation for data base management systems are: massive amount of data, simple repetitive non-numeric operations and the association of a name space with the information space at a high level. The current systems meet these requirements by memory management techniques, specially designed application programs and a sophisticated address mapping methods. This accounts for a large software overhead and the resulting semantic gap between the high level language and the underlying machine architecture. To overcome the difficulties of the von Neumann machines, Slotnick suggested the idea of the hardware backend processing by distributing the processing capabilities outside of CPU and among the read/write cells. These cells act as filters which imp rove the system performance by reducing the processing load on the CPU as well as the amount of data transported back and forth between secondary and main storage. The major contribution of this dissertation is the definition of a backend machine architecture ASLM (Associative Search Language Machine) and the development of a query language ASL (Associative Search Language) which is directly executed by the backend machine using built-in hardware algorithms for query processing and associative hardware for name-space resolution. The language ASL is a high level data base language using associative principles for basic operations. The language has been defined based on the relational data model. ASL is relationally complete, and provides complete data independence. ASL provides facilities for query, insertion, detection and update operations on tuples of variable sizes. Moreover, the structure of the statements in ASL are represented in arithmetic expressions like entities called set expressions. ASLM is designed based on cellular organization, a design similar to Slotnick's idea with an important exception. In the design of ASLM, the processing units (cells) are moved into the backend machine. The general strategy in ASLM is based on the pre-search through the data file and then the execution of the operations on the explicit subfiles which are stored in the associative memory. The generation of the subrelations explicitly eliminates the existence of so-called mark bits in some of the previously designed data base machines. Moreover, it provides fast algorithms for international operations such as join. ASLM is also microprogrammable which gives more flexibility to the system. The design of the ASLM differs from the majority of the data base machines based on Slotnick's idea: first, the separation of the cells from the secondary storage will result in a cost effective system in comparison to the other machines. This also eliminates any restriction on the secondary devices. Second, since cells are independent of each other there is no need for interconnection network between the cells. Third, ASLM is implemented by associative memory, the closeness between associative operations and data base operations reduces the existing semantic gap found in the conventional system, and fourth, ASLM is expandable to the MIMD class of machines.

In establishing the impact of formal data management practices on systems and systems development auditing in the context of a corporate data base environment; the most significant aspects of a data base environment as well as the concept of data management were researched. It was established that organisations need to introduce a data management function to ensure the availability and integrity of data for the organisation. It was further established that an effective data management function can fulfil a key role in ensuring the integrity of the overall data base and as such it becomes an important general control on which the auditor can rely. The audit of information systems in a data base environment requires a more "holistic" audit approach and as a result the auditor has to expand the scope of the systems audit to include an evaluation of the overall data base environment. / Auditing / M. Com (Applied Accounting)

published_or_final_version / abstract / toc / Computer Science and Information Systems / Master / Master of Philosophy

published_or_final_version / abstract / Computer Science / Master / Master of Philosophy

No description available.

by Chu, Kam Wing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 67-73). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Related Work --- p.6 / Chapter 3 --- Time-Series Searching with Scaling and Shifting --- p.12 / Chapter 3.1 --- Problem Statement --- p.15 / Chapter 3.2 --- Preliminary --- p.16 / Chapter 3.3 --- Geometrical View of the Problem --- p.18 / Chapter 3.3.1 --- Scale-Shift Transformation --- p.21 / Chapter 3.3.2 --- Determine Scaling Factor and Shifting Offset --- p.24 / Chapter 3.4 --- Algorithm --- p.25 / Chapter 3.4.1 --- MBR Penetration --- p.26 / Chapter 3.4.2 --- Long Sequence --- p.28 / Chapter 3.5 --- Implementation Details --- p.29 / Chapter 3.5.1 --- MBR Penetration Checking --- p.29 / Chapter 3.5.2 --- Dimension Reduction --- p.32 / Chapter 3.6 --- Experimental Results --- p.34 / Chapter 4 --- Metric Space Indexing for Multimedia Databases --- p.38 / Chapter 4.1 --- Preliminaries --- p.39 / Chapter 4.1.1 --- M-tree --- p.39 / Chapter 4.1.2 --- Range Queries --- p.41 / Chapter 4.1.3 --- Nearest Neighbor Queries --- p.44 / Chapter 4.2 --- Nearest Neighbor Search by dmin Only --- p.46 / Chapter 4.3 --- Analysis --- p.50 / Chapter 4.3.1 --- Critical Factor dmin --- p.52 / Chapter 4.4 --- Multiple Bounding Regions --- p.54 / Chapter 4.4.1 --- Computing Multiple Bounding Regions --- p.56 / Chapter 4.4.2 --- New Insert Strategy --- p.58 / Chapter 4.5 --- Experimental Results --- p.58 / Chapter 5 --- Conclusions --- p.64 / Chapter 5.1 --- Time-Series Searching with Scaling and Shifting --- p.64 / Chapter 5.2 --- Metric Space Indexing --- p.65 / Bibliography --- p.67

Cheung Ching Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 71-73). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Biological Sequences --- p.2 / Chapter 1.2 --- User Queries on Biological Sequences --- p.4 / Chapter 1.3 --- Research Contributions --- p.6 / Chapter 1.4 --- Organization of Thesis --- p.6 / Chapter 2 --- Background --- p.7 / Chapter 2.1 --- What is a Suffix-Tree? --- p.7 / Chapter 2.2 --- Disk-Based Suffix-Trees --- p.9 / Chapter 3 --- Disk-Based Suffix Tree Constructions --- p.11 / Chapter 3.1 --- An Existing Algorithm: PrePar-Suff ix --- p.11 / Chapter 3.1.1 --- "Three Issues: Edge Splitting, Random Access and Data Skew" --- p.13 / Chapter 3.2 --- DynaCluster-Suffix: A New Novel Disk-Based Suffix-Tree Construction Algorithm --- p.18 / Chapter 4 --- Suffix Links Rebuilt --- p.29 / Chapter 4.1 --- Suffix-links and Least Common Ancestors --- p.29 / Chapter 5 --- q-Length Exact Sequence Matching --- p.35 / Chapter 5.1 --- q-Length Exact Sequence Matching by Suffix-Tree --- p.35 / Chapter 6 --- Implementation --- p.38 / Chapter 6.1 --- System Overview --- p.38 / Chapter 6.1.1 --- Index Builder --- p.39 / Chapter 6.1.2 --- Exact Query Processor --- p.39 / Chapter 6.1.3 --- Suffix Links Regenerator --- p.40 / Chapter 6.1.4 --- Tandem Repeats Finder --- p.40 / Chapter 6.2 --- Data Structures --- p.40 / Chapter 6.2.1 --- Representation of a Node --- p.40 / Chapter 6.2.2 --- An Alternative Node Representation --- p.42 / Chapter 6.2.3 --- Representation of a Leaf --- p.43 / Chapter 6.3 --- Buffering --- p.44 / Chapter 6.3.1 --- Page Format --- p.44 / Chapter 6.3.2 --- Address Translation --- p.45 / Chapter 6.3.3 --- Page Replacement Strategies --- p.45 / Chapter 7 --- A Performance Studies --- p.48 / Chapter 7.1 --- When Everything Can be Held In Memory --- p.52 / Chapter 7.2 --- When Main Memory Is Limited --- p.54 / Chapter 7.3 --- The Effectiveness of DNA Lengths with Fixed Memory Sizes . --- p.56 / Chapter 7.4 --- The Effectiveness of Memory Sizes --- p.57 / Chapter 7.5 --- Answering q-Length Exact Sequence Matching Queries --- p.60 / Chapter 7.6 --- Suffix Link Rebuilt --- p.61 / Chapter 8 --- Conclusions and Future Works --- p.69 / Chapter 8.1 --- Conclusions --- p.69 / Chapter 8.2 --- Future Works --- p.70 / Bibliography --- p.71

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