954 resultados para String-pulling


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The semantic web vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input, and returns answers drawn from one or more knowledge bases (KBs). We say that AquaLog is portable because the configuration time required to customize the system for a particular ontology is negligible. AquaLog presents an elegant solution in which different strategies are combined together in a novel way. It makes use of the GATE NLP platform, string metric algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target KB. Moreover it also includes a learning component, which ensures that the performance of the system improves over the time, in response to the particular community jargon used by end users.

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The paper discusses the application of a similarity metric based on compression to the measurement of the distance among Bulgarian dia- lects. The similarity metric is de ned on the basis of the notion of Kolmo- gorov complexity of a le (or binary string). The application of Kolmogorov complexity in practice is not possible because its calculation over a le is an undecidable problem. Thus, the actual similarity metric is based on a real life compressor which only approximates the Kolmogorov complexity. To use the metric for distance measurement of Bulgarian dialects we rst represent the dialectological data in such a way that the metric is applicable. We propose two such representations which are compared to a baseline distance between dialects. Then we conclude the paper with an outline of our future work.

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The biggest threat to any business is a lack of timely and accurate information. Without all the facts, businesses are pressured to make critical decisions and assess risks and opportunities based largely on guesswork, sometimes resulting in financial losses and missed opportunities. The meteoric rise of Databases (DB) appears to confirm the adage that “information is power”, but the stark reality is that information is useless if one has no way to find what one needs to know. It is more accurate perhaps to state that, “the ability to find information is power”. In this paper we show how Instantaneous Database Access System (IDAS) can make a crucial difference by pulling data together and allowing users to summarise information quickly from all areas of a business organisation.

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Intrusion detection is a critical component of security information systems. The intrusion detection process attempts to detect malicious attacks by examining various data collected during processes on the protected system. This paper examines the anomaly-based intrusion detection based on sequences of system calls. The point is to construct a model that describes normal or acceptable system activity using the classification trees approach. The created database is utilized as a basis for distinguishing the intrusive activity from the legal one using string metric algorithms. The major results of the implemented simulation experiments are presented and discussed as well.

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The result of the distributed computing projectWieferich@Home is presented: the binary periodic numbers of bit pseudo-length j ≤ 3500 obtained by replication of a bit string of bit pseudo-length k ≤ 24 and increased by one are Wieferich primes only for the cases of 1092 or 3510.

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For a fibre Raman amplifier with randomly varying birefringence, we provide insight on the validity of previously explored multi-scale techniques leading to polarisation pulling of the signal state of polarisation to the pump state of polarisation. Unlike previous study, we demonstrate that in addition to polarisation pulling a new random birefringence-mediated phenomenon that goes beyond existing multi-scale techniques can boost resonance-like gain fluctuations similar to the Stochastic Anti-Resonance. For mode locked fibre lasers we report on fast and slow polarisation dynamics of fundamental, bound state, and multipulsing vector solitons along with stretched pulses. We demonstrate that tuning cavity anisotropy and birefringence along with parameters of an injected signal with randomly varying state of polarisation provides access to the variety of vector waveforms previously unexplored.

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Stochastic anti-resonance, that is resonant enhancement of randomness caused by polarization mode beatings, is analyzed both numerically and analytically on an example of fibre Raman amplifier with randomly varying birefringence. As a result of such anti-resonance, the polarization mode dispersion growth causes an escape of the signal state of polarization from a metastable state corresponding to the pulling of the signal to the pump state of polarization.This phenomenon reveals itself in abrupt growth of gain fluctuations as well as in dropping of Hurst parameter and Kramers length characterizing long memory in a system and noise induced escape from the polarization pulling state. The results based on analytical multiscale averaging technique agree perfectly with the numerical data obtained by direct numerical simulations of underlying stochastic differential equations. This challenging outcome would allow replacing the cumbersome numerical simulations for real-world extra-long high-speed communication systems.

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We report on a theoretical study of polarization impairments in periodically spun fiber Raman amplifiers. Based on the Stochastic Generator approach we have derived equations for polarization dependent gain and mean-square gain fluctuations. We show that periodically spun fiber can work as a Raman polarizer but it suffers from increased polarization dependent gain and gain fluctuations. Unlike this, application of a depolarizer can result in suppression of polarization dependent gain and gain fluctuations. We demonstrate that it is possible to design a new fiber Raman polarizer by combining a short fiber without spin and properly chosen parameters and a long periodically spun fiber. This polarizer provides almost the same polarization pulling for all input signal states of polarization and so have very small polarization dependent gain. The obtained results can be used in high-speed fiber optic communication for design of quasi-isotropic spatially and spectrally transparent media with increased Raman gain. © 2011 IEEE.

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Photovoltaic (PV) stations have been widely built in the world to utilize solar energy directly. In order to reduce the capital and operational costs, early fault diagnosis is playing an increasingly important role by enabling the long effective operation of PV arrays. This paper analyzes the terminal characteristics of faulty PV strings and arrays, and it develops a PV array fault diagnosis technique. The terminal current-voltage curve of a faulty PV array is divided into two sections, i.e., high-voltage and low-voltage fault diagnosis sections. The corresponding working points of healthy string modules and of healthy and faulty modules in an unhealthy string are then analyzed for each section. By probing into different working points, a faulty PV module can be located. The fault information is of critical importance for the maximum power point tracking and the array dynamical reconfiguration. Furthermore, the string current sensors can be eliminated, and the number of voltage sensors can be reduced by optimizing voltage sensor locations. Typical fault scenarios including monostring, multistring, and a partial shadow for a 1.6-kW 3 $times$ 3 PV array are presented and experimentally tested to confirm the effectiveness of the proposed fault diagnosis method.

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Photovoltaic (PV) solar power generation is proven to be effective and sustainable but is currently hampered by relatively high costs and low conversion efficiency. This paper addresses both issues by presenting a low-cost and efficient temperature distribution analysis for identifying PV module mismatch faults by thermography. Mismatch faults reduce the power output and cause potential damage to PV cells. This paper first defines three fault categories in terms of fault levels, which lead to different terminal characteristics of the PV modules. The investigation of three faults is also conducted analytically and experimentally, and maintenance suggestions are also provided for different fault types. The proposed methodology is developed to combine the electrical and thermal characteristics of PV cells subjected to different fault mechanisms through simulation and experimental tests. Furthermore, the fault diagnosis method can be incorporated into the maximum power point tracking schemes to shift the operating point of the PV string. The developed technology has improved over the existing ones in locating the faulty cell by a thermal camera, providing a remedial measure, and maximizing the power output under faulty conditions.

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This thesis addressed the problem of risk analysis in mental healthcare, with respect to the GRiST project at Aston University. That project provides a risk-screening tool based on the knowledge of 46 experts, captured as mind maps that describe relationships between risks and patterns of behavioural cues. Mind mapping, though, fails to impose control over content, and is not considered to formally represent knowledge. In contrast, this thesis treated GRiSTs mind maps as a rich knowledge base in need of refinement; that process drew on existing techniques for designing databases and knowledge bases. Identifying well-defined mind map concepts, though, was hindered by spelling mistakes, and by ambiguity and lack of coverage in the tools used for researching words. A novel use of the Edit Distance overcame those problems, by assessing similarities between mind map texts, and between spelling mistakes and suggested corrections. That algorithm further identified stems, the shortest text string found in related word-forms. As opposed to existing approaches’ reliance on built-in linguistic knowledge, this thesis devised a novel, more flexible text-based technique. An additional tool, Correspondence Analysis, found patterns in word usage that allowed machines to determine likely intended meanings for ambiguous words. Correspondence Analysis further produced clusters of related concepts, which in turn drove the automatic generation of novel mind maps. Such maps underpinned adjuncts to the mind mapping software used by GRiST; one such new facility generated novel mind maps, to reflect the collected expert knowledge on any specified concept. Mind maps from GRiST are stored as XML, which suggested storing them in an XML database. In fact, the entire approach here is ”XML-centric”, in that all stages rely on XML as far as possible. A XML-based query language allows user to retrieve information from the mind map knowledge base. The approach, it was concluded, will prove valuable to mind mapping in general, and to detecting patterns in any type of digital information.

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With the exponential increasing demands and uses of GIS data visualization system, such as urban planning, environment and climate change monitoring, weather simulation, hydrographic gauge and so forth, the geospatial vector and raster data visualization research, application and technology has become prevalent. However, we observe that current web GIS techniques are merely suitable for static vector and raster data where no dynamic overlaying layers. While it is desirable to enable visual explorations of large-scale dynamic vector and raster geospatial data in a web environment, improving the performance between backend datasets and the vector and raster applications remains a challenging technical issue. This dissertation is to implement these challenging and unimplemented areas: how to provide a large-scale dynamic vector and raster data visualization service with dynamic overlaying layers accessible from various client devices through a standard web browser, and how to make the large-scale dynamic vector and raster data visualization service as rapid as the static one. To accomplish these, a large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling and a comprehensive performance improvement solution are proposed, designed and implemented. They include: the quadtree-based indexing and parallel map tiling, the Legend String, the vector data visualization with dynamic layers overlaying, the vector data time series visualization, the algorithm of vector data rendering, the algorithm of raster data re-projection, the algorithm for elimination of superfluous level of detail, the algorithm for vector data gridding and re-grouping and the cluster servers side vector and raster data caching.

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Florida International University Commencement Ceremony December 13,2010 at US Century Bank Arena ( Session 3) Graduates and their guests wait for the ceremony to begin.Additionally, the FIU String Quartet plays for the audience.

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The purpose of this study was to investigate the efficacy of using monosodium glutamate (MSG) as a means to increase palatability and prospective consumption of vegetables at a congregate meal site with Cuban-American clients. Thirty to 32 subjects participated in hedonic testing each day. MSG-enhanced (2 g MSG/500 g vegetable) and non-enhanced beets, string beans, carrots and peas were evaluated for palatability, preference and prospective consumption. Results showed that MSG significantly increased both palatability and prospective consumption of string beans (ps < .05) but not of the other 3 vegetables tested. These findings provide some evidence that MSG can be used to increase the palatability of vegetables served at congregate meal sites. However, these results suggest that older adults may not find the palatability of some vegetables to be improved by MSG and that optimal flavor enhancement cannot be achieved by adding the same amount of MSG to every vegetable.

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Water and gas is a common by - product of the oil production process. Production may be compromised by the precipitation of inorganic salts in both the reservoir and producing well, through scale formation. This precipitation is likely the cause of the formation damage. High temperatures and h igh pressures (HTHP) may favor the precipitation of insoluble salts. The most common types of scale in oil fields are calcium carbonate and calcium sulphate, strontium and barium sulphate. New types of scale formation have attracted special attention such as zinc sulphide and lead. This precipitation may occur in the pores of reservoir rocks, in the production string and in equipment, causing obstructions and consequent production losses. In this study, the influence of well depth on incrustation compositio n was investigated to design removal treatments and assess the behavior of these deposits along the string, through the analysis of pressure and temperature. Scale residues were recovered from the inside of the production string of an oil and gas well duri ng the string removal operation. A total of 10 samples from different depths (15.4 m to 4061.5 m) were obtained. Initially a dissolution test was conducted in weak acid, similar to that used in removal operations with this type of scale formation. Majority composition was defined and confirmed by dissolution tests using X - Ray Fluorescence Spectroscopy (XRF), X - Ray Diffraction (XRD) and Scanning Electron Microscope (SEM) techniques. Residues with distinct characteristics were observed in different proportion s, showing a tendency toward increased and/or decreased mass with depth. In the samples closest to the surface, typical sandstone residues were found, with calcium (45% Ca) as the metal of highest concentration. The obtained results indicate correlations o f the scale types studied with the depth and, consequently, with the thermodynamic conditions of pressure and temperature.