1000 resultados para Database


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Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

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Public buildings and large infrastructure are typically monitored by tens or hundreds of cameras, all capturing different physical spaces and observing different types of interactions and behaviours. However to date, in large part due to limited data availability, crowd monitoring and operational surveillance research has focused on single camera scenarios which are not representative of real-world applications. In this paper we present a new, publicly available database for large scale crowd surveillance. Footage from 12 cameras for a full work day covering the main floor of a busy university campus building, including an internal and external foyer, elevator foyers, and the main external approach are provided; alongside annotation for crowd counting (single or multi-camera) and pedestrian flow analysis for 10 and 6 sites respectively. We describe how this large dataset can be used to perform distributed monitoring of building utilisation, and demonstrate the potential of this dataset to understand and learn the relationship between different areas of a building.

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Visual information in the form of lip movements of the speaker has been shown to improve the performance of speech recognition and search applications. In our previous work, we proposed cross database training of synchronous hidden Markov models (SHMMs) to make use of external large and publicly available audio databases in addition to the relatively small given audio visual database. In this work, the cross database training approach is improved by performing an additional audio adaptation step, which enables audio visual SHMMs to benefit from audio observations of the external audio models before adding visual modality to them. The proposed approach outperforms the baseline cross database training approach in clean and noisy environments in terms of phone recognition accuracy as well as spoken term detection (STD) accuracy.

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Speech recognition can be improved by using visual information in the form of lip movements of the speaker in addition to audio information. To date, state-of-the-art techniques for audio-visual speech recognition continue to use audio and visual data of the same database for training their models. In this paper, we present a new approach to make use of one modality of an external dataset in addition to a given audio-visual dataset. By so doing, it is possible to create more powerful models from other extensive audio-only databases and adapt them on our comparatively smaller multi-stream databases. Results show that the presented approach outperforms the widely adopted synchronous hidden Markov models (HMM) trained jointly on audio and visual data of a given audio-visual database for phone recognition by 29% relative. It also outperforms the external audio models trained on extensive external audio datasets and also internal audio models by 5.5% and 46% relative respectively. We also show that the proposed approach is beneficial in noisy environments where the audio source is affected by the environmental noise.

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This article uses topological approaches to suggest that education is becoming-topological. Analyses presented in a recent double-issue of Theory, Culture & Society are used to demonstrate the utility of topology for education. In particular, the article explains education's topological character through examining the global convergence of education policy, testing and the discursive ranking of systems, schools and individuals in the promise of reforming education through the proliferation of regimes of testing at local and global levels that constitute a new form of governance through data. In this conceptualisation of global education policy changes in the form and nature of testing combine with it the emergence of global policy network to change the nature of the local (national, regional, school and classroom) forces that operate through the ‘system’. While these forces change, they work through a discursivity that produces disciplinary effects, but in a different way. This new–old disciplinarity, or ‘database effect’, is here represented through a topological approach because of its utility for conceiving education in an increasingly networked world.

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Fossils provide the principal basis for temporal calibrations, which are critical to the accuracy of divergence dating analyses. Translating fossil data into minimum and maximum bounds for calibrations is the most important, and often least appreciated, step of divergence dating. Properly justified calibrations require the synthesis of phylogenetic, paleontological, and geological evidence and can be difficult for non-specialists to formulate. The dynamic nature of the fossil record (e.g., new discoveries, taxonomic revisions, updates of global or local stratigraphy) requires that calibration data be updated continually lest they become obsolete. Here, we announce the Fossil Calibration Database (http://fossilcalibrations.org), a new open-access resource providing vetted fossil calibrations to the scientific community. Calibrations accessioned into this database are based on individual fossil specimens and follow best practices for phylogenetic justification and geochronological constraint. The associated Fossil Calibration Series, a calibration-themed publication series at Palaeontologia Electronica, will serve as one key pipeline for peer-reviewed calibrations to enter the database.

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With new national targets for patient flow in public hospitals designed to increase efficiencies in patient care and resource use, better knowledge of events affecting length of stay will support improved bed management and scheduling of procedures. This paper presents a case study involving the integration of material from each of three databases in operation at one tertiary hospital and demonstrates it is possible to follow patient journeys from admission to discharge. What is known about this topic? At present, patient data at one Queensland tertiary hospital are assembled in three information systems: (1) the Hospital Based Corporate Information System (HBCIS), which tracks patients from in-patient admission to discharge; (2) the Emergency Department Information System (EDIS) containing patient data from presentation to departure from the emergency department; and (3) Operation Room Management Information System (ORMIS), which records surgical operations. What does this paper add? This paper describes how a new enquiry tool may be used to link the three hospital information systems for studying the hospital journey through different wards and/or operating theatres for both individual and groups of patients. What are the implications for practitioners? An understanding of the patients’ journeys provides better insight into patient flow and provides the tool for research relating to access block, as well as optimising the use of physical and human resources.

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This paper describes the design and implementation of a high-level query language called Generalized Query-By-Rule (GQBR) which supports retrieval, insertion, deletion and update operations. This language, based on the formalism of database logic, enables the users to access each database in a distributed heterogeneous environment, without having to learn all the different data manipulation languages. The compiler has been implemented on a DEC 1090 system in Pascal.

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This paper describes the design and implementation of ADAMIS (‘A database for medical information systems’). ADAMIS is a relational database management system for a general hospital environment. Apart from the usual database (DB) facilities of data definition and data manipulation, ADAMIS supports a query language called the ‘simplified medical query language’ (SMQL) which is completely end-user oriented and highly non-procedural. Other features of ADAMIS include provision of facilities for statistics collection and report generation. ADAMIS also provides adequate security and integrity features and has been designed mainly for use on interactive terminals.

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Database management systems offer a very reliable and attractive data organization for fast and economical information storage and processing for diverse applications. It is much more important that the information should be easily accessible to users with varied backgrounds, professional as well as casual, through a suitable data sublanguage. The language adopted here (APPLE) is one such language for relational database systems and is completely nonprocedural and well suited to users with minimum or no programming background. This is supported by an access path model which permits the user to formulate completely nonprocedural queries expressed solely in terms of attribute names. The data description language (DDL) and data manipulation language (DML) features of APPLE are also discussed. The underlying relational database has been implemented with the help of the DATATRIEVE-11 utility for record and domain definition which is available on the PDP-11/35. The package is coded in Pascal and MACRO-11. Further, most of the limitations of the DATATRIEVE-11 utility have been eliminated in the interface package.

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In this paper the main features of ARDBID (A Relational Database for Interactive Design) have been described. An overview of the organization of the database has been presented and a detailed description of the data definition and manipulation languages has been given. These have been implemented on a DEC 1090 system.

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The benefits that accrue from the use of design database include (i) reduced costs of preparing data for application programs and of producing the final specification, and (ii) possibility of later usage of data stored in the database for other applications related to Computer Aided Engineering (CAE). An INTEractive Relational GRAphics Database (INTERGRAD) based on relational models has been developed to create, store, retrieve and update the data related to two dimensional drawings. INTERGRAD provides two languages, Picture Definition Language (PDL) and Picture Manipulation Language (PML). The software package has been implemented on a PDP 11/35 system under the RSX-11M version 3.1 operating system and uses the graphics facility consisting of a VT-11 graphics terminal, the DECgraphic 11 software and an input device, a lightpen.

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This article discusses the design and development of GRDB (General Purpose Relational Data Base System) which has been implemented on a DEC-1090 system in Pascal. GRDB is a general purpose database system designed to be completely independent of the nature of data to be handled, since it is not tailored to the specific requirements of any particular enterprise. It can handle different types of data such as variable length records and textual data. Apart from the usual database facilities such as data definition and data manipulation, GRDB supports User Definition Language (UDL) and Security definition language. These facilities are provided through a SEQUEL-like General Purpose Query Language (GQL). GRDB provides adequate protection facilities up to the relation level. The concept of “security matrix” has been made use of to provide database protection. The concept of Unique IDentification number (UID) and Password is made use of to ensure user identification and authentication. The concept of static integrity constraints has been used to ensure data integrity. Considerable efforts have been made to improve the response time through indexing on the data files and query optimisation. GRDB is designed for an interactive use but alternate provision has been made for its use through batch mode also. A typical Air Force application (consisting of data about personnel, inventory control, and maintenance planning) has been used to test GRDB and it has been found to perform satisfactorily.