200 resultados para parsing


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The web services (WS) technology provides a comprehensive solution for representing, discovering, and invoking services in a wide variety of environments, including Service Oriented Architectures (SOA) and grid computing systems. At the core of WS technology lie a number of XML-based standards, such as the Simple Object Access Protocol (SOAP), that have successfully ensured WS extensibility, transparency, and interoperability. Nonetheless, there is an increasing demand to enhance WS performance, which is severely impaired by XML's verbosity. SOAP communications produce considerable network traffic, making them unfit for distributed, loosely coupled, and heterogeneous computing environments such as the open Internet. Also, they introduce higher latency and processing delays than other technologies, like Java RMI and CORBA. WS research has recently focused on SOAP performance enhancement. Many approaches build on the observation that SOAP message exchange usually involves highly similar messages (those created by the same implementation usually have the same structure, and those sent from a server to multiple clients tend to show similarities in structure and content). Similarity evaluation and differential encoding have thus emerged as SOAP performance enhancement techniques. The main idea is to identify the common parts of SOAP messages, to be processed only once, avoiding a large amount of overhead. Other approaches investigate nontraditional processor architectures, including micro-and macrolevel parallel processing solutions, so as to further increase the processing rates of SOAP/XML software toolkits. This survey paper provides a concise, yet comprehensive review of the research efforts aimed at SOAP performance enhancement. A unified view of the problem is provided, covering almost every phase of SOAP processing, ranging over message parsing, serialization, deserialization, compression, multicasting, security evaluation, and data/instruction-level processing.

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Matita (that means pencil in Italian) is a new interactive theorem prover under development at the University of Bologna. When compared with state-of-the-art proof assistants, Matita presents both traditional and innovative aspects. The underlying calculus of the system, namely the Calculus of (Co)Inductive Constructions (CIC for short), is well-known and is used as the basis of another mainstream proof assistant—Coq—with which Matita is to some extent compatible. In the same spirit of several other systems, proof authoring is conducted by the user as a goal directed proof search, using a script for storing textual commands for the system. In the tradition of LCF, the proof language of Matita is procedural and relies on tactic and tacticals to proceed toward proof completion. The interaction paradigm offered to the user is based on the script management technique at the basis of the popularity of the Proof General generic interface for interactive theorem provers: while editing a script the user can move forth the execution point to deliver commands to the system, or back to retract (or “undo”) past commands. Matita has been developed from scratch in the past 8 years by several members of the Helm research group, this thesis author is one of such members. Matita is now a full-fledged proof assistant with a library of about 1.000 concepts. Several innovative solutions spun-off from this development effort. This thesis is about the design and implementation of some of those solutions, in particular those relevant for the topic of user interaction with theorem provers, and of which this thesis author was a major contributor. Joint work with other members of the research group is pointed out where needed. The main topics discussed in this thesis are briefly summarized below. Disambiguation. Most activities connected with interactive proving require the user to input mathematical formulae. Being mathematical notation ambiguous, parsing formulae typeset as mathematicians like to write down on paper is a challenging task; a challenge neglected by several theorem provers which usually prefer to fix an unambiguous input syntax. Exploiting features of the underlying calculus, Matita offers an efficient disambiguation engine which permit to type formulae in the familiar mathematical notation. Step-by-step tacticals. Tacticals are higher-order constructs used in proof scripts to combine tactics together. With tacticals scripts can be made shorter, readable, and more resilient to changes. Unfortunately they are de facto incompatible with state-of-the-art user interfaces based on script management. Such interfaces indeed do not permit to position the execution point inside complex tacticals, thus introducing a trade-off between the usefulness of structuring scripts and a tedious big step execution behavior during script replaying. In Matita we break this trade-off with tinycals: an alternative to a subset of LCF tacticals which can be evaluated in a more fine-grained manner. Extensible yet meaningful notation. Proof assistant users often face the need of creating new mathematical notation in order to ease the use of new concepts. The framework used in Matita for dealing with extensible notation both accounts for high quality bidimensional rendering of formulae (with the expressivity of MathMLPresentation) and provides meaningful notation, where presentational fragments are kept synchronized with semantic representation of terms. Using our approach interoperability with other systems can be achieved at the content level, and direct manipulation of formulae acting on their rendered forms is possible too. Publish/subscribe hints. Automation plays an important role in interactive proving as users like to delegate tedious proving sub-tasks to decision procedures or external reasoners. Exploiting the Web-friendliness of Matita we experimented with a broker and a network of web services (called tutors) which can try independently to complete open sub-goals of a proof, currently being authored in Matita. The user receives hints from the tutors on how to complete sub-goals and can interactively or automatically apply them to the current proof. Another innovative aspect of Matita, only marginally touched by this thesis, is the embedded content-based search engine Whelp which is exploited to various ends, from automatic theorem proving to avoiding duplicate work for the user. We also discuss the (potential) reusability in other systems of the widgets presented in this thesis and how we envisage the evolution of user interfaces for interactive theorem provers in the Web 2.0 era.

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Nowadays, there is an increasing interest in wireless sensor networks (WSN) for environmental monitoring systems because it can be used to improve the quality of life and living conditions are becoming a major concern to people. This paper describes the design and development of a real time monitoring system based on ZigBee WSN characterized by a lower energy consumption, low cost, reduced dimensions and fast adaptation to the network tree topology. The developed system encompasses an optimized sensing process about environmental parameters, low rate transmission from sensor nodes to the gateway, packet parsing and data storing in a remote database and real time visualization through a web server.

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[EN]In this paper, a clothes segmentation method for fashion parsing is described. This method does not rely in a previous pose estimation but people segmentation. Therefore, novel and classic segmentation techniques have been considered and improved in order to achieve accurate people segmentation. Unlike other methods described in the literature, the output is the bounding box and the predominant color of the different clothes and not a pixel level segmentation. The proposal is based on dividing the person area into an initial fixed number of stripes, that are later fused according to similar color distribution. To assess the quality of the proposed method the experiments are carried out with the Fashionista dataset that is widely used in the fashion parsing community.

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Ontology design and population -core aspects of semantic technologies- re- cently have become fields of great interest due to the increasing need of domain-specific knowledge bases that can boost the use of Semantic Web. For building such knowledge resources, the state of the art tools for ontology design require a lot of human work. Producing meaningful schemas and populating them with domain-specific data is in fact a very difficult and time-consuming task. Even more if the task consists in modelling knowledge at a web scale. The primary aim of this work is to investigate a novel and flexible method- ology for automatically learning ontology from textual data, lightening the human workload required for conceptualizing domain-specific knowledge and populating an extracted schema with real data, speeding up the whole ontology production process. Here computational linguistics plays a fundamental role, from automati- cally identifying facts from natural language and extracting frame of relations among recognized entities, to producing linked data with which extending existing knowledge bases or creating new ones. In the state of the art, automatic ontology learning systems are mainly based on plain-pipelined linguistics classifiers performing tasks such as Named Entity recognition, Entity resolution, Taxonomy and Relation extraction [11]. These approaches present some weaknesses, specially in capturing struc- tures through which the meaning of complex concepts is expressed [24]. Humans, in fact, tend to organize knowledge in well-defined patterns, which include participant entities and meaningful relations linking entities with each other. In literature, these structures have been called Semantic Frames by Fill- 6 Introduction more [20], or more recently as Knowledge Patterns [23]. Some NLP studies has recently shown the possibility of performing more accurate deep parsing with the ability of logically understanding the structure of discourse [7]. In this work, some of these technologies have been investigated and em- ployed to produce accurate ontology schemas. The long-term goal is to collect large amounts of semantically structured information from the web of crowds, through an automated process, in order to identify and investigate the cognitive patterns used by human to organize their knowledge.

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Grammars for programming languages are traditionally specified statically. They are hard to compose and reuse due to ambiguities that inevitably arise. PetitParser combines ideas from scannerless parsing, parser combinators, parsing expression grammars and packrat parsers to model grammars and parsers as objects that can be reconfigured dynamically. Through examples and benchmarks we demonstrate that dynamic grammars are not only flexible but highly practical.

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Mr. Kubon's project was inspired by the growing need for an automatic, syntactic analyser (parser) of Czech, which could be used in the syntactic processing of large amounts of texts. Mr. Kubon notes that such a tool would be very useful, especially in the field of corpus linguistics, where creating a large-scale "tree bank" (a collection of syntactic representations of natural language sentences) is a very important step towards the investigation of the properties of a given language. The work involved in syntactically parsing a whole corpus in order to get a representative set of syntactic structures would be almost inconceivable without the help of some kind of robust (semi)automatic parser. The need for the automatic natural language parser to be robust increases with the size of the linguistic data in the corpus or in any other kind of text which is going to be parsed. Practical experience shows that apart from syntactically correct sentences, there are many sentences which contain a "real" grammatical error. These sentences may be corrected in small-scale texts, but not generally in the whole corpus. In order to be able to complete the overall project, it was necessary to address a number of smaller problems. These were; 1. the adaptation of a suitable formalism able to describe the formal grammar of the system; 2. the definition of the structure of the system's dictionary containing all relevant lexico-syntactic information, and the development of a formal grammar able to robustly parse Czech sentences from the test suite; 3. filling the syntactic dictionary with sample data allowing the system to be tested and debugged during its development (about 1000 words); 4. the development of a set of sample sentences containing a reasonable amount of grammatical and ungrammatical phenomena covering some of the most typical syntactic constructions being used in Czech. Number 3, building a formal grammar, was the main task of the project. The grammar is of course far from complete (Mr. Kubon notes that it is debatable whether any formal grammar describing a natural language may ever be complete), but it covers the most frequent syntactic phenomena, allowing for the representation of a syntactic structure of simple clauses and also the structure of certain types of complex sentences. The stress was not so much on building a wide coverage grammar, but on the description and demonstration of a method. This method uses a similar approach as that of grammar-based grammar checking. The problem of reconstructing the "correct" form of the syntactic representation of a sentence is closely related to the problem of localisation and identification of syntactic errors. Without a precise knowledge of the nature and location of syntactic errors it is not possible to build a reliable estimation of a "correct" syntactic tree. The incremental way of building the grammar used in this project is also an important methodological issue. Experience from previous projects showed that building a grammar by creating a huge block of metarules is more complicated than the incremental method, which begins with the metarules covering most common syntactic phenomena first, and adds less important ones later, especially from the point of view of testing and debugging the grammar. The sample of the syntactic dictionary containing lexico-syntactical information (task 4) now has slightly more than 1000 lexical items representing all classes of words. During the creation of the dictionary it turned out that the task of assigning complete and correct lexico-syntactic information to verbs is a very complicated and time-consuming process which would itself be worth a separate project. The final task undertaken in this project was the development of a method allowing effective testing and debugging of the grammar during the process of its development. The problem of the consistency of new and modified rules of the formal grammar with the rules already existing is one of the crucial problems of every project aiming at the development of a large-scale formal grammar of a natural language. This method allows for the detection of any discrepancy or inconsistency of the grammar with respect to a test-bed of sentences containing all syntactic phenomena covered by the grammar. This is not only the first robust parser of Czech, but also one of the first robust parsers of a Slavic language. Since Slavic languages display a wide range of common features, it is reasonable to claim that this system may serve as a pattern for similar systems in other languages. To transfer the system into any other language it is only necessary to revise the grammar and to change the data contained in the dictionary (but not necessarily the structure of primary lexico-syntactic information). The formalism and methods used in this project can be used in other Slavic languages without substantial changes.

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Brian electric activity is viewed as sequences of momentary maps of potential distribution. Frequency-domain source modeling, estimation of the complexity of the trajectory of the mapped brain field distributions in state space, and microstate parsing were used as analysis tools. Input-presentation as well as task-free (spontaneous thought) data collection paradigms were employed. We found: Alpha EEG field strength is more affected by visualizing mentation than by abstract mentation, both input-driven as well as self-generated. There are different neuronal populations and brain locations of the electric generators for different temporal frequencies of the brain field. Different alpha frequencies execute different brain functions as revealed by canonical correlations with mentation profiles. Different modes of mentation engage the same temporal frequencies at different brain locations. The basic structure of alpha electric fields implies inhomogeneity over time — alpha consists of concatenated global microstates in the sub-second range, characterized by quasi-stable field topographies, and rapid transitions between the microstates. In general, brain activity is strongly discontinuous, indicating that parsing into field landscape-defined microstates is appropriate. Different modes of spontaneous and induced mentation are associated with different brain electric microstates; these are proposed as candidates for psychophysiological ``atoms of thought''.

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This paper addresses the problem of service development based on GSM handset signaling. The aim is to achieve this goal without the participation of the users, which requires the use of a passive GSM receiver on the uplink. Since no tool for GSM uplink capturing was available, we developed a new method that can synchronize to multiple mobile devices by simply overhearing traffic between them and the network. Our work includes the implementation of modules for signal recovery, message reconstruction and parsing. The method has been validated against a benchmark solution on GSM downlink and independently evaluated on uplink channels. Initial evaluations show up to 99% success rate in message decoding, which is a very promising result. Moreover, we conducted measurements that reveal insights on the impact of signal power on the capturing performance and investigate possible reactive measures.

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Software corpora facilitate reproducibility of analyses, however, static analysis for an entire corpus still requires considerable effort, often duplicated unnecessarily by multiple users. Moreover, most corpora are designed for single languages increasing the effort for cross-language analysis. To address these aspects we propose Pangea, an infrastructure allowing fast development of static analyses on multi-language corpora. Pangea uses language-independent meta-models stored as object model snapshots that can be directly loaded into memory and queried without any parsing overhead. To reduce the effort of performing static analyses, Pangea provides out-of-the box support for: creating and refining analyses in a dedicated environment, deploying an analysis on an entire corpus, using a runner that supports parallel execution, and exporting results in various formats. In this tool demonstration we introduce Pangea and provide several usage scenarios that illustrate how it reduces the cost of analysis.

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Code clone detection helps connect developers across projects, if we do it on a large scale. The cornerstones that allow clone detection to work on a large scale are: (1) bad hashing (2) lightweight parsing using regular expressions and (3) MapReduce pipelines. Bad hashing means to determine whether or not two artifacts are similar by checking whether their hashes are identical. We show a bad hashing scheme that works well on source code. Lightweight parsing using regular expressions is our technique of obtaining entire parse trees from regular expressions, robustly and efficiently. We detail the algorithm and implementation of one such regular expression engine. MapReduce pipelines are a way of expressing a computation such that it can automatically and simply be parallelized. We detail the design and implementation of one such MapReduce pipeline that is efficient and debuggable. We show a clone detector that combines these cornerstones to detect code clones across all projects, across all versions of each project.

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The efficiency of the biological pump of carbon to the deep ocean depends largely on the biologically mediated export of carbon from the surface ocean and its remineralization with depth. Global satellite studies have primarily focused on chlorophyll concentration and net primary production (NPP) to understand the role of phytoplankton in these processes. Recent satellite retrievals of phytoplankton composition now allow for the size of phytoplankton cells to be considered. Here, we improve understanding of phytoplankton size structure impacts on particle export, remineralization and transfer. Particulate organic carbon (POC) flux observations from sediment traps and 234Th are compiled across the global ocean. Annual climatologies of NPP, percent microplankton, and POC flux at four time series locations and within biogeochemical provinces are constructed, and sinking velocities are calculated to align surface variables with POC flux at depth. Parameters that characterize POC flux vs. depth (export flux ratio, labile fraction, remineralization length scale) are then fit to the aligned dataset. Times of the year dominated by different size compositions are identified and fit separately in regions of the ocean where phytoplankton cell size showed enough dynamic range over the annual cycle. Considering all data together, our findings support the paradigm of high export flux but low transfer efficiency in more productive regions and vice versa for oligotrophic regions. However, when parsing by dominant size class, we find periods dominated by small cells to have both greater export flux and lower transfer efficiency than periods when large cells comprise a greater proportion of the phytoplankton community.

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A video-aware unequal loss protection (ULP) system for protecting RTP video streaming in bursty packet loss networks is proposed. Just considering the relevance of the frame, the state of the channel and the bitrate constraints of the protection bitstream, our algorithm selects in real time the most suitable frames to be protected through forward error correction (FEC) techniques. It benefits from a wise RTP encapsulation that allows working at a frame level without requiring any further process than that of parsing RTP headers, so it is perfectly suitable to be included in commercial transmitters. The simulation results show how our proposed ULP technique outperforms non-smart schemes.

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We discuss from a practical point of view a number of ssues involved in writing distributed Internet and WWW applications using LP/CLP systems. We describe PiLLoW, a publicdomain Internet and WWW programming library for LP/CLP systems that we have designed in order to simplify the process of writing such applications. PiLLoW provides facilities for accessing documents and code on the WWW; parsing, manipulating and generating HTML and XML structured documents and data; producing HTML forms; writing form handlers and CGI-scripts; and processing HTML/XML templates. An important contribution of PÍ'LLOW is to model HTML/XML code (and, thus, the content of WWW pages) as terms. The PÍ'LLOW library has been developed in the context of the Ciao Prolog system, but it has been adapted to a number of popular LP/CLP systems, supporting most of its functionality. We also describe the use of concurrency and a highlevel model of client-server interaction, Ciao Prolog's active modules, in the context of WWW programming. We propose a solution for client-side downloading and execution of Prolog code, using generic browsers. Finally, we also provide an overview of related work on the topic.

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A number of data description languages initially designed as standards for trie WWW are currently being used to implement user interfaces to programs. This is done independently of whether such programs are executed in the same or a different host as trie one running the user interface itself. The advantage of this approach is that it provides a portable, standardized, and easy to use solution for the application programmer, and a familiar behavior for the user, typically well versed in the use of WWW browsers. Among the proposed standard description languages, VRML is a aimed at representing three dimensional scenes including hyperlink capabilities. VRML is already used as an import/export format in many 3-D packages and tools, and has been shown effective in displaying complex objects and scenarios. We propose and describe a Prolog library which allows parsing and checking VRML code, transforming it, and writing it out as VRML again. The library converts such code to an internal representation based on first order terms which can then be arbitrarily manipulated. We also present as an example application the use of this library to implement a novel 3-D visualization for examining and understanding certain aspects of the behavior of CLP(FD) programs.