983 resultados para Database System for Alumni Tracking


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Satisfiability, implication and equivalence problems are important and widely-encountered database problems that need to be efficiently and effectively solved. We provide a comprehensive and systematic study of these problems. We consider three popular types of arithmetic inequalities, (X op C), (X op Y), and (X op Y + C), where X and Y are attributes, C is a constant of the domain of X, and op $\in\ \{{<},\ {\le},\ {=},\ {\not=},\ {>},\ {\ge}\}.$ These inequalities are most frequently used in a database system, since the first type of inequalities represents $\theta$-join, the second type represents selection, and the third type is popular in deductive databases. We study the problems under the integer domain and the real domain, as well as under two different operator sets.^ Our results show that solutions under different domains and/or different operator sets are quite different. In this dissertation, we either report the first necessary and sufficient conditions as well as their efficient algorithms with complexity analysis, or provide improved algorithms. ^

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Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles’ location and motion information, range queries on current and history data, and prediction of vehicles’ movement in the near future. To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed.

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Today, databases have become an integral part of information systems. In the past two decades, we have seen different database systems being developed independently and used in different applications domains. Today's interconnected networks and advanced applications, such as data warehousing, data mining & knowledge discovery and intelligent data access to information on the Web, have created a need for integrated access to such heterogeneous, autonomous, distributed database systems. Heterogeneous/multidatabase research has focused on this issue resulting in many different approaches. However, a single, generally accepted methodology in academia or industry has not emerged providing ubiquitous intelligent data access from heterogeneous, autonomous, distributed information sources. This thesis describes a heterogeneous database system being developed at Highperformance Database Research Center (HPDRC). A major impediment to ubiquitous deployment of multidatabase technology is the difficulty in resolving semantic heterogeneity. That is, identifying related information sources for integration and querying purposes. Our approach considers the semantics of the meta-data constructs in resolving this issue. The major contributions of the thesis work include: (i.) providing a scalable, easy-to-implement architecture for developing a heterogeneous multidatabase system, utilizing Semantic Binary Object-oriented Data Model (Sem-ODM) and Semantic SQL query language to capture the semantics of the data sources being integrated and to provide an easy-to-use query facility; (ii.) a methodology for semantic heterogeneity resolution by investigating into the extents of the meta-data constructs of component schemas. This methodology is shown to be correct, complete and unambiguous; (iii.) a semi-automated technique for identifying semantic relations, which is the basis of semantic knowledge for integration and querying, using shared ontologies for context-mediation; (iv.) resolutions for schematic conflicts and a language for defining global views from a set of component Sem-ODM schemas; (v.) design of a knowledge base for storing and manipulating meta-data and knowledge acquired during the integration process. This knowledge base acts as the interface between integration and query processing modules; (vi.) techniques for Semantic SQL query processing and optimization based on semantic knowledge in a heterogeneous database environment; and (vii.) a framework for intelligent computing and communication on the Internet applying the concepts of our work.

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Calibration of movement tracking systems is a difficult problem faced by both animals and robots. The ability to continuously calibrate changing systems is essential for animals as they grow or are injured, and highly desirable for robot control or mapping systems due to the possibility of component wear, modification, damage and their deployment on varied robotic platforms. In this paper we use inspiration from the animal head direction tracking system to implement a self-calibrating, neurally-based robot orientation tracking system. Using real robot data we demonstrate how the system can remove tracking drift and learn to consistently track rotation over a large range of velocities. The neural tracking system provides the first steps towards a fully neural SLAM system with improved practical applicability through selftuning and adaptation.

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This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

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Introduction: The built environment is increasingly recognised as being associated with health outcomes. Relationships between the built environment and health differ among age groups, especially between children and adults, but also between younger, mid-age and older adults. Yet few address differences across life stage groups within a single population study. Moreover, existing research mostly focuses on physical activity behaviours, with few studying objective clinical and mental health outcomes. The Life Course Built Environment and Health (LCBEH) project explores the impact of the built environment on self-reported and objectively measured health outcomes in a random sample of people across the life course. Methods and analysis: This cross-sectional data linkage study involves 15 954 children (0–15 years), young adults (16–24 years), adults (25–64 years) and older adults (65+years) from the Perth metropolitan region who completed the Health and Wellbeing Surveillance System survey administered by the Department of Health of Western Australia from 2003 to 2009. Survey data were linked to Western Australia's (WA) Hospital Morbidity Database System (hospital admission) and Mental Health Information System (mental health system outpatient) data. Participants’ residential address was geocoded and features of their ‘neighbourhood’ were measured using Geographic Information Systems software. Associations between the built environment and self-reported and clinical health outcomes will be explored across varying geographic scales and life stages. Ethics and dissemination: The University of Western Australia's Human Research Ethics Committee and the Department of Health of Western Australia approved the study protocol (#2010/1). Findings will be published in peer-reviewed journals and presented at local, national and international conferences, thus contributing to the evidence base informing the design of healthy neighbourhoods for all residents.

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Background The measurement of severity and control of asthma in both children and adults can be based on subjective or objective measures. It has been advocated that fractional exhaled nitric oxide (FeNO) can be used to monitor airway inflammation as it correlates with some markers of asthma. Interventions for asthma therapies have been traditionally based on symptoms and/or spirometry. Objectives To evaluate the efficacy of tailoring asthma interventions based on exhaled nitric oxide in comparison to clinical symptoms (with or without spirometry/peak flow) for asthma related outcomes in children and adults. Search methods We searched the Cochrane Airways Group Specialised Register of Trials, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE and reference lists of articles. The last search was completed in February 2009. Selection criteria All randomised controlled comparisons of adjustment of asthma therapy based on exhaled nitric oxide compared to traditional methods (primarily clinical symptoms and spirometry/peak flow). Data collection and analysis Results of searches were reviewed against pre-determined criteria for inclusion. Relevant studies were independently selected in duplicate. Two authors independently assessed trial quality and extracted data. Authors were contacted for further information with response from one. Main results Two studies have been added for this update, which now includes six (2 adults and 4 children/adolescent) studies; these studies differed in a variety of ways including definition of asthma exacerbations, FeNO cut off levels, the way in which FeNO was used to adjust therapy and duration of study. Of 1053 participants randomised, 1010 completed the trials. In the meta-analysis, there was no significant difference between groups for the primary outcome of asthma exacerbations or for other outcomes (clinical symptoms, FeNO level and spirometry). In post-hoc analysis, a significant reduction in mean final daily dose inhaled corticosteroid per adult was found in the group where treatment was based on FeNO in comparison to clinical symptoms, (mean difference -450 mcg; 95% CI -677 to -223 mcg budesonide equivalent/day). However, the total amount of inhaled corticosteroid used in one of the adult studies was 11% greater in the FeNO arm. In contrast, in the paediatric studies, there was a significant increase in inhaled corticosteroid dose in the FeNO strategy arm (mean difference of 140 mcg; 95% CI 29 to 251, mcg budesonide equivalent/day). Authors' conclusions Tailoring the dose of inhaled corticosteroids based on exhaled nitric oxide in comparison to clinical symptoms was carried out in different ways in the six studies and found only modest benefit at best and potentially higher doses of inhaled corticosteroids in children. The role of utilising exhaled nitric oxide to tailor the dose of inhaled corticosteroids cannot be routinely recommended for clinical practice at this stage and remains uncertain.

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We study how probabilistic reasoning and inductive querying can be combined within ProbLog, a recent probabilistic extension of Prolog. ProbLog can be regarded as a database system that supports both probabilistic and inductive reasoning through a variety of querying mechanisms. After a short introduction to ProbLog, we provide a survey of the different types of inductive queries that ProbLog supports, and show how it can be applied to the mining of large biological networks.

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To effectively support today’s global economy, database systems need to manage data in multiple languages simultaneously. While current database systems do support the storage and management of multilingual data, they are not capable of querying across different natural languages. To address this lacuna, we have recently proposed two cross-lingual functionalities, LexEQUAL[13] and SemEQUAL[14], for matching multilingual names and concepts, respectively. In this paper, we investigate the native implementation of these multilingual functionalities as first-class operators on relational engines. Specifically, we propose a new multilingual storage datatype, and an associated algebra of the multilingual operators on this datatype. These components have been successfully implemented in the PostgreSQL database system, including integration of the algebra with the query optimizer and inclusion of a metric index in the access layer. Our experiments demonstrate that the performance of the native implementation is up to two orders-of-magnitude faster than the corresponding outsidethe- server implementation. Further, these multilingual additions do not adversely impact the existing functionality and performance. To the best of our knowledge, our prototype represents the first practical implementation of a crosslingual database query engine.

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In this report, we investigate the problem of applying a range constraint in order to reduce the systematic heading drift in a foot-mounted inertial navigation system (INS) (motion-tracking). We make use of two foot-mounted INS, one on each foot, which are aided with zero-velocity detectors. A novel algorithm is proposed in order to reduce the systematic heading drift. The proposed algorithm is based on the idea that the separation between the two feet at any given instance must always lie within a sphere of radius equal to the maximum possible spatial separation between the two feet. A Kalman filter, getting one measurement update and two observation updates is used in this algorithm.

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Este trabalho objetivou traçar um percurso analítico da base institucional e material da gestão da arborização na cidade do Rio de Janeiro, visando a adoção de procedimentos para a quantificação do carbono armazenado nas árvores na malha urbana para possibilitar o conhecimento sobre o arboreto e o estabelecimento de objetivos quantificáveis, reportáveis e verificáveis de redução de emissões de gases de efeito estufa. Com a instituição da obrigatoriedade em nível nacional da metas de redução das emissões de gases de efeito estufa, através da Lei n 12.187/09, o município do Rio de Janeiro oficializou legalmente, com a Lei Muncipal n 5.248/11, o compromisso de adoção de medidas e programas de incentivo para reduzir as emissões de gases de efeito estufa na cidade. Entretanto, a única ação de mitigação controlada pelo município, com procedimentos regulamentados, é a compensação de emissões nas construções através do plantio de árvores. O acompanhamento da execução dos plantios de árvores, exigidos no licenciamento das construções é a atual forma de estabelecer objetivos quantificáveis, reportáveis e verificáveis de redução de emissões antrópicas de gases de efeito estufa no Município. De forma específica, foi realizada uma análise dos recursos institucionais e materiais disponíveis e potenciais à disposição do sistema de planejamento e gestão ambiental do município, com a proposição de criar um sistema de banco de dados (SGBD) da arborização urbana. O banco de dados estruturado ao longo da pesquisa, foi utilizado em um sistema de informação geográfico (SIG), onde foi possível realizar um estudo exploratório da estimativa de estoque de carbono em árvores em logradouros. A investigação desta pesquisa teve dupla expectativa: contribuir para a eficácia das ações de manejo e controle do arboreto urbano, com base no monitoramento contínuo dos serviços ambientais das árvores; e consolidar critérios analíticos habilitados para quantificar as alterações de fitomassa do arboreto urbano, em uma proposta de um plano de arborização para a cidade, até agora inexistente, que foi delineado ao final do trabalho, que seguramente irá garantir significativos benefícios ambientais, econômicos e sociais à sociedade.

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在总结了现有并行数据库实现模型的基础上,基于"半重写变换"模型[1]实现了一个并行数据库系统的原型。通过对数据划分/重划分、并行选择、并行排序、并行连接等关键操作的实验分析,指出了"半重写变换"模型存在的缺陷,并提出了一种混合式的改进模型。从理论上说,在机群架构下实现并行数据库系统,这种混合模型较单一模型更有优势。

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多级安全数据库的安全策略需要各种模型来表达,访问控制模型是其中之一.强制访问控制(MAC)模型保证多级数据库中的信息流动符合系统的安全策略.利用基于角色的访问控制(RBAC)来实现MAC能方便多级安全数据库的权限管理.提出了一种MAC与RBAC的综合模型,定义了多级角色与内部角色的概念,并给出了综合模型中经过修改后的操作,使得系统能自动地完成符合强制访问控制策略的用户权限的管理.该模型方便了管理员的权限管理,适合用户较多,安全层次比较复杂的多级关系数据库系统.最后给出了模型的部分实现机制.

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提出了在DBMS中支持多种安全策略的需求,指出了在DBMS中支持多安全策略所面临的主要问题,针对这些问题提出了支持多安全策略的DBMS体系结构(MSDA).在抽象层次上该体系结构与GFAC一致,主要区别表现在性能优化和面向DBMS的适应性改造.为了提高系统性能,MSDA在客体管理器中引入了访问判定缓存.而为了适用于DBMS,MSDA在体系结构层次引入了重写来支持高效的细粒度访问控制.此外还引入了访问上下文栈来支持视图和存储过程这类的受控访问机制.给出了MSDA在LOIS SDBMS v3.0中的实现,并通过实验给出了MSDA对目标系统的性能影响分析.结果表明,MSDA将访问控制判定与实施分离,既能充分解决数据库系统中支持多安全策略的相关问题,同时能够与当前主流关系数据库系统相匹配,不会造成目标系统性能的显著下降.