The purpose of this thesis is to develop a web-enabled database which facilitates research related connections and communication among Naval Postgraduate School (NPS) students, professors and DOD organizations. The proposed name for the prototype website is the Joint Online Thesis and Research System (JOTARS). The specific functional objectives of JOTARS are to establish standard infrastructure and processes that allow DOD organizations to dynamically propose research topics, view research in progress, and a means to suggest topics for class projects. JOTARS will also enable NPS students to conduct refined searches of proposed research topics.

Approved for public release, distribution unlimited / The purpose of this thesis is to conduct the research necessary to develop integrated 3D terrain maps capable of supporting an Unmanned Aerial Vehicle Flight Mission Control Support System. In this work, the author has tried to explore the feasibility of exploiting digital topographic maps and further understanding of the digital terrain support available to UAV FMCSS developers. This thesis explores numerous digital terrain data representations and tools available to create digital environments. This work examines and gives a methodology how to find, process, and operate in these environments. To accomplish this, the author explores the more general problem of where to find the data, what tools are available, and how to put the pieces together to create a registered digital environment on a state-of-the-art computer. This work provides a logical construct and design methodology for an analyst to create high fidelity terrain data sets. It functions as a â how toâ manual to help analysts understand which information and tools are available to use for different types of simulation projects.

The thesis focuses on the phenomenon of databases from the normative viewpoint; it examines them with respe to the legal issues, main stress being placed on the prote ion granted to databases by the intelle ual property law and on their incorporation in the legal system of the Czech Republic. The merit of the thesis can be seen in elaborating on decisions of the Court of Justice of the European Union regarding the harmonised regulations and in drawing a comparison to the provisions of the dire ive on legal prote ion of databases (or rather the Copyright A ) and analysing the impa of the decisions. The thesis is organised into eleven chapters, Chapter Two providing a brief introdu ion into the topic of databases, Chapter Three looking into the international-law aspe of databases. The core of the thesis lies in Chapters Four to Chapter Eight which give an insight into the European law, its secondary sources followed by a discourse on the dire ive on the legal prote ion of databases, regarding the copyright element and sui generis right as well as a criticism of the dire ive resulting in it being reviewed by the Commission. Chapter Nine pays attention to alternative means of database prote ion. The nal chapters evaluate the current state in the eld of database prote ion and suggest possible suitable...

The topic of this diploma thesis is copyright protection of databases. The aim of the thesis is to describe and introduce databases and their legal protection due to their role as essential tools for the location of required information. The thesis contains analysis of legislation in European Union and the Czech Republic and includes brief analysis of legislation in Finland. The thesis consists of five chapters. The first chapter deals with the term database, classification of databases and illustrates basic foundations for database protection. The second chapter is divided into two subchapters and characterises the legal protection of databases in European Union. The first subchapter is concerned with the legislation process and adoption of the directive on the legal protection of databases starting with the Green Paper in 1988 and ending with adoption of the directive in 1996. The second subchapter analyses this directive in more detail, describes the main terms and institutes and explores the two-tier system of legal protection of databases introduced by this directive. The third chapter presents legislation in Finland with regard to the exchange studies of the author of the thesis and outlines the catalogue rule as a traditional element of Scandinavian law. The fourth chapter is divided into...

Este trabalho dá as bases para a criação de um sistema computacional, gráfico-interativo, de apoio ao ordenamento territorial. Dada a complexidade e multiplicidade de dados exigidos nesta área, parte do princípio de que a Cartografia Temática, nos seus moldes tradicionais, não tem meios de atender às necessidades das Geociências, na disposição e representação de forma integrada dos resultados de suas análises. Uma plataforma de informações, informatizada, nesta área, vem ao encontro das expectativas das instituições de pesquisa ambiental, posto que proporciona o aproveitamento efetivo de seus estudos aplicados. Da mesma forma, constitui uma importante ferramenta de trabalho para os órgãos ligados ao planejamento, à tomada de decisão e à monitoria. Posiciona o ordenamento territorial quanto à sua definição, como compreendido atualmente, e, quanto a conceitos praticados, quando de seu surgimento, por volta dos anos 60, como conseqüência dos estudos regionais realizados. Uma tentativa de situar seu campo de ação é feita, em meio a novas terminologias, abordagens e conceitos decorrentes da retomada do interesse da Sociedade na utilização ordenada de seu território. Lança as bases para a implantação de um sistema de apoio ao ordenamento territorial, indicando algumas atitudes compreensivas e apontando principais procedimentos. Com a modelagem do sistema, através de diagramas e fluxogramas, chega-se à estruturação dos arquivos de dados, apoiando-se numa simulação de incorporação de subsídios. Utiliza como objeto da simulação, o diagnóstico ambiental realizado pelo Instituto Brasileiro de Geografia e Estatística - IBGE, para a bacia do rio Itapecuru, no Estado do Maranhão. A simulação é encerrada com um teste de funcionalidade da estrutura proposta, por meio de consultas que buscam a agregação dos dados para pesquisas específicas. / Establishes the basis for the creation of a computerized, graphics-interactive territorial arrangement support system. Given the complexity and multiplicity of data required in this field, it is based in the fact that Thematic Cartography - in its traditional form - does not fulfill the needs of Geosciences, failing to provide a integrated representation of its analyses\' findings. Such a computerized database, in this field, meets the needs of environmental research institutions, allowing the actual employment of its applied work. At the same time, it also establishes an important working tool for agencies in charge of planning, decision-making and monitoring. Contextualizes territorial arrangement, according to its perception today and in terms of concepts in practice that date back to its appearance, consequence of regional studies conducted during the 1960s. Attempts to assess its action domain, in our time, in the midst of the arrival of new terminology approaches and concepts - as a result of Society\'s interest retrieval in the ordained use of territory. Lays the foundation for the implementation of a territorial arrangement support system, its comprehensive behavior, structure and key procedures. Enables the shaping of the system, through diagrams and flow charts, followed by the database configuration, based on a real-life simulation of information collection. As the replicated matter, it applies the environmental diagnoses of the Itapecuru River basin, in the Brazilian state of Maranhão, prepared by the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística - IBGE). Completes the simulation with an operational test of the proposed system, through research that seeks data integration in specific studies.

Yu-shan Chan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 95-99). / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1 --- "Expert System, Expert System Shell, and ""MetaSystem""" --- p.2 / Chapter 1.2 --- Adopting OBJECTBASE In EXPERT SYSTEM SHELL(ESS) --- p.4 / Chapter 2. --- SURVEY ON EXISTING SYSTEMS --- p.7 / Chapter 2.1 --- Review of inference models --- p.7 / Chapter 2.1.1 --- The Classical Period --- p.9 / Chapter 2.1.2 --- The modern period --- p.11 / Chapter 2.2 --- Rules in Objectbase vs. other Representations --- p.12 / Chapter 2.2.1 --- Rule-based systems --- p.13 / Chapter 2.2.2 --- Object-oriented systems --- p.13 / Chapter 2.2.3 --- Other systems --- p.13 / Chapter 2.2.4 --- Rules embedded in object-- the Objectbase approach --- p.14 / Chapter 2.3 --- Conclusion --- p.15 / Chapter 3. --- DESIGN OF ESS FOR AN OBJECTBASE SYSTEM --- p.16 / Chapter 3.1 --- Introducing ESS in Objectbase --- p.18 / Chapter 3.1.1 --- The Concept of Object Modeling --- p.19 / Chapter 3.1.2 --- Why Objectbase? --- p.20 / Chapter 3.1.3 --- ESS : a higher layer on Objectbase --- p.22 / Chapter 3.1.4 --- Schema Objects and Shell Objects --- p.23 / Chapter 3.2 --- Module design of ESS --- p.24 / Chapter 3.2.1 --- Knowledge Representation Module --- p.25 / Chapter 3.2.2 --- Objectbase inference module --- p.27 / Chapter 3.2.3 --- The Rule一Inference Module --- p.28 / Chapter 3.3 --- Knowledge Representation --- p.29 / Chapter 3.3.1 --- Schema Knowledge & the Rulebase --- p.30 / Chapter 3.3.2 --- Rule Structure --- p.31 / Chapter 3.4 --- Inference Engine --- p.35 / Chapter 3.4.1 --- The Two Levels of Inference --- p.35 / Chapter 3.5 --- Rule一Inference (RI) --- p.37 / Chapter 3.5.1 --- Structural design of RI --- p.38 / Chapter 3.5.2 --- Drawing Inference --- p.39 / Chapter 3.5.3 --- Query Processor and RI --- p.42 / Chapter 3.5.4 --- RI and the Inference Engine(IE) --- p.43 / Chapter 3.6 --- Conclusion --- p.43 / Chapter 4. --- IMPLEMENTATION --- p.45 / Chapter 4.1 --- Rulelnference: a comprehensive structure --- p.46 / Chapter 4.1.1 --- Class Rule --- p.46 / Chapter 4.1.2 --- Class RuleList --- p.47 / Chapter 4.1.3 --- Accompany data structures for inference --- p.48 / Chapter 4.1.4 --- Class Rulelnference --- p.49 / Chapter 4.2 --- Rule Setting --- p.51 / Chapter 4.2.1 --- Rule Construction --- p.51 / Chapter 4.2.2 --- Rule Parsing and the Rule Definition Language (RDL) --- p.52 / Chapter 4.3 --- How Inference is done in ESS --- p.53 / Chapter 4.3.1 --- Reset and Load system --- p.53 / Chapter 4.3.2 --- Inference making --- p.54 / Chapter 4.4 --- Using RuleInference in the Rule Constructor --- p.58 / Chapter 4.4.1 --- The Rule Constructor --- p.59 / Chapter 4.5 --- Using Rulelnference in the Application Constructor --- p.60 / Chapter 4.5.1 --- The RiNode --- p.61 / Chapter 4.5.2 --- Schema and Rule Set Handling --- p.63 / Chapter 4.6 --- Conclusion --- p.64 / Chapter 5. --- CASE STUDY --- p.66 / Chapter 5.1 --- Background on Statement analysis --- p.66 / Chapter 5.1.1 --- Ratios for decision making --- p.68 / Chapter 5.2 --- Sample System: Financial Data Analysis System --- p.70 / Chapter 5.2.1 --- The FINANCE schema --- p.71 / Chapter 5.2.2 --- Rules --- p.73 / Chapter 5.2.3 --- Results --- p.75 / Chapter 5.3 --- Evaluation --- p.81 / Chapter 5.4 --- Conclusion --- p.82 / Chapter 6. --- RESULT AND DISCUSSION --- p.84 / Chapter 6.1 --- An Expert System Shell on Objectbase --- p.84 / Chapter 6.2 --- The ESS on MOBILE --- p.85 / Chapter 6.3 --- Pros and cons for the ESS --- p.86 / Chapter 6.4 --- MOBILE: how it has been improved --- p.87 / Chapter 7. --- CONCLUSION --- p.89 / Chapter 7.1 --- Comparison --- p.91 / Chapter 7.2 --- Appraisal --- p.92 / Chapter 8. --- REFERENCES --- p.95 / Table of Content for Appendixes / APPENDIX 1. RULE DEFINITION LANGUAGE --- p.100 / APPENDIX 2. THE CLASS RULEINFERENCE --- p.103 / APPENDIX 3. THE RINODE --- p.104 / APPENDIX 4. FINANCIAL STATEMENT ANALYSIS --- p.108 / APPENDIX 5. DATA STRUCTURE OF RULE AND RULELIST --- p.117 / APPENDIX 6. DATA STRUCTURE OF VARLIST AND ACTLIST --- p.118 / APPENDIX 7. DATA STRUCTURE OF RULEINFERENCE --- p.121

Jessie Ching. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1989. / Bibliography: leaves 98-101.

by Yan, Men-Hin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 114-119). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgments --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Storing XML in Database Systems --- p.2 / Chapter 1.2 --- Outline of the Thesis --- p.4 / Chapter 2 --- Related Work --- p.5 / Chapter 2.1 --- Overview of XML --- p.5 / Chapter 2.1.1 --- Extensible Markup Language (XML) --- p.5 / Chapter 2.1.2 --- Data Type Definition (DTD) --- p.6 / Chapter 2.1.3 --- "ID, IDREF and IDREFS" --- p.9 / Chapter 2.2 --- Using Special-Purpose Database to Store XML Data --- p.10 / Chapter 2.3 --- Using Relational Databases to Store XML Data --- p.11 / Chapter 2.3.1 --- Extracting Schemas with STORED --- p.11 / Chapter 2.3.2 --- Using Simple Schemes Based on Labeled Graph --- p.12 / Chapter 2.3.3 --- Generating Schemas from DTDs --- p.12 / Chapter 2.3.4 --- Commercial Approaches --- p.13 / Chapter 2.4 --- Discovering Functional Dependencies --- p.14 / Chapter 2.4.1 --- Functional Dependency --- p.14 / Chapter 2.4.2 --- Finding Functional Dependencies --- p.14 / Chapter 2.4.3 --- TANE and Partition Refinement --- p.15 / Chapter 2.5 --- Multivalued Dependencies --- p.17 / Chapter 2.5.1 --- Example of Multivalued Dependency --- p.18 / Chapter 3 --- Using RDBMS to Store XML Data --- p.20 / Chapter 3.1 --- Global Schema Extraction Algorithm --- p.22 / Chapter 3.1.1 --- Step 1: Simplify DTD --- p.22 / Chapter 3.1.2 --- Step 2: Construct Schema Prototype Trees --- p.24 / Chapter 3.1.3 --- Step 3: Generate Relational Schema Prototype --- p.29 / Chapter 3.1.4 --- Step 4: Discover Functional Dependencies and Candidate Keys --- p.31 / Chapter 3.1.5 --- Step 5: Normalize the Relational Schema Prototypes --- p.32 / Chapter 3.1.6 --- Discussion --- p.32 / Chapter 3.2 --- DTD-splitting Schema Extraction Algorithm --- p.34 / Chapter 3.2.1 --- Step 1: Simplify DTD --- p.35 / Chapter 3.2.2 --- Step 2: Construct Schema Prototype Trees --- p.36 / Chapter 3.2.3 --- Step 3: Generate Relational Schema Prototype --- p.45 / Chapter 3.2.4 --- Step 4: Discover Functional Dependencies and Candidate Keys --- p.46 / Chapter 3.2.5 --- Step 5: Normalize the Relational Schema Prototypes --- p.47 / Chapter 3.2.6 --- Discussion --- p.49 / Chapter 3.3 --- Experimental Results --- p.50 / Chapter 3.3.1 --- Real Life XML Data: SIGMOD Record XML --- p.50 / Chapter 3.3.2 --- Synthetic XML Data --- p.58 / Chapter 3.3.3 --- Discussion --- p.68 / Chapter 4 --- Finding Multivalued Dependencies --- p.75 / Chapter 4.1 --- Validation of Multivalued Dependencies --- p.77 / Chapter 4.2 --- Search Strategy and Pruning --- p.80 / Chapter 4.2.1 --- Search Strategy for Left-hand Sides Candidates --- p.81 / Chapter 4.2.2 --- Search Strategy for Right-hand Sides Candidates --- p.82 / Chapter 4.2.3 --- Other Pruning --- p.85 / Chapter 4.3 --- Computing with Partitions --- p.87 / Chapter 4.3.1 --- Computing Partitions --- p.88 / Chapter 4.4 --- Algorithm --- p.89 / Chapter 4.4.1 --- Generating Next Level Candidates --- p.92 / Chapter 4.4.2 --- Computing Partitions --- p.93 / Chapter 4.5 --- Experimental Results --- p.94 / Chapter 4.5.1 --- Results of the Algorithm --- p.95 / Chapter 4.5.2 --- Evaluation on the Results --- p.96 / Chapter 4.5.3 --- Scalability of the Algorithm --- p.98 / Chapter 4.5.4 --- Using Multivalued Dependencies in Schema Extraction Al- gorithms --- p.101 / Chapter 5 --- Conclusion --- p.108 / Chapter 5.1 --- Discussion --- p.108 / Chapter 5.2 --- Future Work --- p.110 / Chapter 5.2.1 --- Translate Semistructured Queries to SQL --- p.110 / Chapter 5.2.2 --- Improve the Multivalued Dependency Discovery Algorithm --- p.112 / Chapter 5.2.3 --- Incremental Update of Resulting Schema --- p.113 / Bibliography --- p.113 / Appendix --- p.120 / Chapter A --- Simple Proof for Minimality in Multivalued Dependencies --- p.120 / Chapter B --- Third and Fourth Normal Form Decompositions --- p.122 / Chapter B.1 --- 3NF Decomposition Algorithm --- p.123 / Chapter B.2 --- 4NF Decomposition Algorithm --- p.124

Cai, Junpu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 49-51). / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Related Works --- p.6 / Chapter 3 --- Problem Definition --- p.10 / Chapter 4 --- Preliminary Study --- p.14 / Chapter 5 --- Algorithms --- p.17 / Chapter 5.1 --- Result Caching algorithm --- p.17 / Chapter 5.1.1 --- Caching Algorithm --- p.18 / Chapter 5.1.2 --- Implementation and Maintenance --- p.20 / Chapter 5.2 --- Query Processing algorithm --- p.20 / Chapter 5.2.1 --- Join Types --- p.21 / Chapter 5.2.2 --- Operators in the Operator Tree --- p.23 / Chapter 5.2.3 --- Comparison with previous work --- p.27 / Chapter 5.2.4 --- Operator Tree (OT) for one CN --- p.28 / Chapter 5.2.5 --- Generic Operator Network (ON) --- p.30 / Chapter 6 --- Empirical Study --- p.37 / Chapter 6.1 --- Result Caching --- p.38 / Chapter 6.2 --- Comparison of Bushy and Left Deep Plans --- p.41 / Chapter 6.3 --- Comparison of ON and previous methods --- p.44 / Chapter 7 --- Conclusion and Future Work --- p.47 / Bibliography --- p.49

A common problem when running Web-based applications is how to scale-up the database. The solution to this problem usually involves having a smart Database Administrator determine how to spread the database tables out amongst computers that will work in parallel. Laying out database tables across multiple machines so they can act together as a single efficient database is hard. Automated methods are needed to help eliminate the time required for database administrators to create optimal configurations. There are four operators that we consider that can create a search space of possible database layouts: 1) denormalizing, 2) horizontally partitioning, 3) vertically partitioning, and 4) fully replicating. Textbooks offer general advice that is useful for dealing with extreme cases - for instance you should fully replicate a table if the level of insert to selects is close to zero. But even this seemingly obvious statement is not necessarily one that will lead to a speed up once you take into account that some nodes might be a bottle neck. There can be complex interactions between the 4 different operators which make it even more difficult to predict what the best thing to do is. Instead of using best practices to do database layout, we need a system that collects empirical data on when these 4 different operators are effective. We have implemented a state based search technique to try different operators, and then we used the empirically measured data to see if any speed up occurred. We recognized that the costs of creating the physical database layout are potentially large, but it is necessary since we want to know the "Ground Truth" about what is effective and under what conditions. After creating a dataset where these four different operators have been applied to make different databases, we can employ machine learning to induce rules to help govern the physical design of the database across an arbitrary number of computer nodes. This learning process, in turn, would allow the database placement algorithm to get better over time as it trains over a set of examples. What this algorithm calls for is that it will try to learn 1) "What is a good database layout for a particular application given a query workload?" and 2) "Can this algorithm automatically improve itself in making recommendations by using machine learned rules to try to generalize when it makes sense to apply each of these operators?" There has been considerable research done in parallelizing databases where large amounts of data are shipped from one node to another to answer a single query. Sometimes the costs of shipping the data back and forth might be high, so in this work we assume that it might be more efficient to create a database layout where each query can be answered by a single node. To make this assumption requires that all the incoming query templates are known beforehand. This requirement can easily be satisfied in the case of a Web-based application due to the characteristic that users typically interact with the system through a web interface such as web forms. In this case, unseen queries are not necessarily answerable, without first possibly reconstructing the data on a single machine. Prior knowledge of these exact query templates allows us to select the best possible database table placements across multiple nodes. But in the case of trying to improve the efficiency of a Web-based application, a web site provider might feel that they are willing to suffer the inconvenience of not being able to answer an arbitrary query, if they are in turn provided with a system that runs more efficiently.