970 resultados para document server


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Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets.

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The problem of projecting multidimensional data into lower dimensions has been pursued by many researchers due to its potential application to data analyses of various kinds. This paper presents a novel multidimensional projection technique based on least square approximations. The approximations compute the coordinates of a set of projected points based on the coordinates of a reduced number of control points with defined geometry. We name the technique Least Square Projections ( LSP). From an initial projection of the control points, LSP defines the positioning of their neighboring points through a numerical solution that aims at preserving a similarity relationship between the points given by a metric in mD. In order to perform the projection, a small number of distance calculations are necessary, and no repositioning of the points is required to obtain a final solution with satisfactory precision. The results show the capability of the technique to form groups of points by degree of similarity in 2D. We illustrate that capability through its application to mapping collections of textual documents from varied sources, a strategic yet difficult application. LSP is faster and more accurate than other existing high-quality methods, particularly where it was mostly tested, that is, for mapping text sets.

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The TCABR data analysis and acquisition system has been upgraded to support a joint research programme using remote participation technologies. The architecture of the new system uses Java language as programming environment. Since application parameters and hardware in a joint experiment are complex with a large variability of components, requirements and specification solutions need to be flexible and modular, independent from operating system and computer architecture. To describe and organize the information on all the components and the connections among them, systems are developed using the extensible Markup Language (XML) technology. The communication between clients and servers uses remote procedure call (RPC) based on the XML (RPC-XML technology). The integration among Java language, XML and RPC-XML technologies allows to develop easily a standard data and communication access layer between users and laboratories using common software libraries and Web application. The libraries allow data retrieval using the same methods for all user laboratories in the joint collaboration, and the Web application allows a simple graphical user interface (GUI) access. The TCABR tokamak team in collaboration with the IPFN (Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade Tecnica de Lisboa) is implementing this remote participation technologies. The first version was tested at the Joint Experiment on TCABR (TCABRJE), a Host Laboratory Experiment, organized in cooperation with the IAEA (International Atomic Energy Agency) in the framework of the IAEA Coordinated Research Project (CRP) on ""Joint Research Using Small Tokamaks"". (C) 2010 Elsevier B.V. All rights reserved.

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This report discusses developing a software log tool for analysis of industrial processes. The target was to develop software that can help electro Engineers for monitor and fault finding in industrial processes. The tool is called PLS (Process log server), and is developed in Visual Studio.NET Framework 2005. PLS works as a client with Beijer Electronics OPC Server. The program is able to read data from PLC (Programmable Logic Controller), trough the OPC Server. PLS connects to all kind of controllers that is supported by the Beijer Electronics OPC Server. Signal data is stored in a database for later analysis. Chosen signals data can easily be exported into a text file. The text file is adopted for import to MS Office Excel. User manual [UM-07] is written as a separate document. The software acted stable through the function test. The final product becomes a first-rate tool that is simple to use. As an advantage, the software can be developed with more functions in the future.

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Being able to ask questions about the provenance of some data requires documentation on each influence on that data's existence and content. Much software exists, and is being developed, for which there is no provenance-awareness, i.e. at best, the data it outputs can be connected to its inputs, but with no record of intermediate processing. Further, where some record of processing does exist, e.g. as logs, it is not in a form easily connected with that of other processes. We would like to enable compiled software to record useful documentation without requiring prior manual adaptation. In this paper, we present an approach to adapting source code from its original form without manual manipulation, to record information on data provenance during execution.

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Documento componente do jogo “Musikinésia (http://www.loa.sead.ufscar.br/musikinesia.php)” desenvolvido pela equipe do Laboratório de Objetos de Aprendizagem da Universidade Federal de São Carlos (LOA/UFSCar).

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Documento componente do jogo “Digestower (http://www.loa.sead.ufscar.br/digestower.php)” desenvolvido pela equipe do Laboratório de Objetos de Aprendizagem da Universidade Federal de São Carlos (LOA/UFSCar).

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Although formal methods can dramatically increase the quality of software systems, they have not widely been adopted in software industry. Many software companies have the perception that formal methods are not cost-effective cause they are plenty of mathematical symbols that are difficult for non-experts to assimilate. The Java Modelling Language (short for JML) Section 3.3 is an academic initiative towards the development of a common formal specification language for Java programs, and the implementation of tools to check program correctness. This master thesis work shows how JML based formal methods can be used to formally develop a privacy sensitive Java application. This is a smart card application for managing medical appointments. The application is named HealthCard. We follow the software development strategy introduced by João Pestana, presented in Section 3.4. Our work influenced the development of this strategy by providing hands-on insight on challenges related to development of a privacy sensitive application in Java. Pestana’s strategy is based on a three-step evolution strategy of software specifications, from informal ones, through semiformal ones, to JML formal specifications. We further prove that this strategy can be automated by implementing a tool that generates JML formal specifications from a welldefined subset of informal software specifications. Hence, our work proves that JML-based formal methods techniques are cost-effective, and that they can be made popular in software industry. Although formal methods are not popular in many software development companies, we endeavour to integrate formal methods to general software practices. We hope our work can contribute to a better acceptance of mathematical based formalisms and tools used by software engineers. The structure of this document is as follows. In Section 2, we describe the preliminaries of this thesis work. We make an introduction to the application for managing medical applications we have implemented. We also describe the technologies used in the development of the application. This section further illustrates the Java Card Remote Method Invocation communication model used in the medical application for the client and server applications. Section 3 introduces software correctness, including the design by contract and the concept of contract in JML. Section 4 presents the design structure of the application. Section 5 shows the implementation of the HealthCard. Section 6 describes how the HealthCard is verified and validated using JML formal methods tools. Section 7 includes some metrics of the HealthCard implementation and specification. Section 8 presents a short example of how a client-side of a smart card application can be implemented while respecting formal specifications. Section 9 describes a prototype tools to generate JML formal specifications from informal specifications automatically. Section 10 describes some challenges and main ideas came acrorss during the development of the HealthCard. The full formal specification and implementation of the HealthCard smart card application presented in this document can be reached at https://sourceforge.net/projects/healthcard/.

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Parmodel is a web server for automated comparative modeling and evaluation of protein structures. The aim of this tool is to help inexperienced users to perform modeling, assessment, visualization, and optimization of protein models as well as crystallographers to evaluate structures solved experimentally. It is subdivided in four modules: Parmodel Modeling, Parmodel Assessment, Parmodel Visualization, and Parmodel Optimization. The main module is the Parmodel Modeling that allows the building of several models ford a same protein in a reduced time, through the distribution of modeling processes on a Beowulf cluster. Parmodel automates and integrates the main softwares used in comparative modeling as MODELLER, Whatcheck, Procheck, Raster3D, Molscript, and Gromacs. This web server is freely accessible at http://www.biocristalografia.df.ibilce.unesp.br/tools/parmodel. (C) 2004 Elsevier B.V. All rights reserved.

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One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for each of the obtained clusters. In many cases the labels have to be built using only the terms in the documents of the collection. This paper presents the SeCLAR (Selecting Candidate Labels using Association Rules) method, which explores the use of association rules for the selection of good candidates for labels of hierarchical document clusters. The candidates are processed by a classical method to generate the labels. The idea of the proposed method is to process each parent-child relationship of the nodes as an antecedent-consequent relationship of association rules. The experimental results show that the proposed method can improve the precision and recall of labels obtained by classical methods. © 2010 Springer-Verlag.

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One way to organize knowledge and make its search and retrieval easier is to create a structural representation divided by hierarchically related topics. Once this structure is built, it is necessary to find labels for each of the obtained clusters. In many cases the labels must be built using all the terms in the documents of the collection. This paper presents the SeCLAR method, which explores the use of association rules in the selection of good candidates for labels of hierarchical document clusters. The purpose of this method is to select a subset of terms by exploring the relationship among the terms of each document. Thus, these candidates can be processed by a classical method to generate the labels. An experimental study demonstrates the potential of the proposed approach to improve the precision and recall of labels obtained by classical methods only considering the terms which are potentially more discriminative. © 2012 - IOS Press and the authors. All rights reserved.