923 resultados para Natural Language Processing,Recommender Systems,Android,Applicazione mobile
Resumo:
This paper is about the use of natural language to communicate with computers. Most researches that have pursued this goal consider only requests expressed in English. A way to facilitate the use of several languages in natural language systems is by using an interlingua. An interlingua is an intermediary representation for natural language information that can be processed by machines. We propose to convert natural language requests into an interlingua [universal networking language (UNL)] and to execute these requests using software components. In order to achieve this goal, we propose OntoMap, an ontology-based architecture to perform the semantic mapping between UNL sentences and software components. OntoMap also performs component search and retrieval based on semantic information formalized in ontologies and rules.
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This article describes the integration of the LSD (Logic for Structure Determination) and SISTEMAT expert systems that were both designed for the computer-assisted structure elucidation of small organic molecules. A first step has been achieved towards the linking of the SISTEMAT database with the LSD structure generator. The skeletal descriptions found by the SISTEMAT programs are now easily transferred to LSD as substructural constraints. Examples of the synergy between these expert systems are given for recently reported natural products.
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The demands of image processing related systems are robustness, high recognition rates, capability to handle incomplete digital information, and magnanimous flexibility in capturing shape of an object in an image. It is exactly here that, the role of convex hulls comes to play. The objective of this paper is twofold. First, we summarize the state of the art in computational convex hull development for researchers interested in using convex hull image processing to build their intuition, or generate nontrivial models. Secondly, we present several applications involving convex hulls in image processing related tasks. By this, we have striven to show researchers the rich and varied set of applications they can contribute to. This paper also makes a humble effort to enthuse prospective researchers in this area. We hope that the resulting awareness will result in new advances for specific image recognition applications.
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The number of research papers available today is growing at a staggering rate, generating a huge amount of information that people cannot keep up with. According to a tendency indicated by the United States’ National Science Foundation, more than 10 million new papers will be published in the next 20 years. Because most of these papers will be available on the Web, this research focus on exploring issues on recommending research papers to users, in order to directly lead users to papers of their interest. Recommender systems are used to recommend items to users among a huge stream of available items, according to users’ interests. This research focuses on the two most prevalent techniques to date, namely Content-Based Filtering and Collaborative Filtering. The first explores the text of the paper itself, recommending items similar in content to the ones the user has rated in the past. The second explores the citation web existing among papers. As these two techniques have complementary advantages, we explored hybrid approaches to recommending research papers. We created standalone and hybrid versions of algorithms and evaluated them through both offline experiments on a database of 102,295 papers, and an online experiment with 110 users. Our results show that the two techniques can be successfully combined to recommend papers. The coverage is also increased at the level of 100% in the hybrid algorithms. In addition, we found that different algorithms are more suitable for recommending different kinds of papers. Finally, we verified that users’ research experience influences the way users perceive recommendations. In parallel, we found that there are no significant differences in recommending papers for users from different countries. However, our results showed that users’ interacting with a research paper Recommender Systems are much happier when the interface is presented in the user’s native language, regardless the language that the papers are written. Therefore, an interface should be tailored to the user’s mother language.
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Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study
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Natural gas, although basically composed by light hydrocarbons, also presents in its composition gaseous contaminants such as CO2 (carbon dioxide) and H2S (hydrogen sulfide). Hydrogen sulfide, which commonly occurs in oil and gas exploration and production activities, besides being among the gases that are responsible by the acid rain and greenhouse effect, can also cause serious harm to health, leading even to death, and damages to oil and natural gas pipelines. Therefore, the removal of hydrogen sulfide will significantly reduce operational costs and will result in oil with best quality to be sent to refinery, thereby resulting in economical, environmental, and social benefits. These factors highlight the need for the development and improvement of hydrogen sulfide sequestrating agents to be used in the oil industry. Nowadays there are several procedures for hydrogen sulfide removal from natural gas used by the petroleum industry. However, they produce derivatives of amines that are harmful to the distillation towers, form insoluble precipitates that cause pipe clogging and produce wastes of high environmental impact. Therefore, the obtaining of a stable system, in inorganic or organic reaction media, that is able to remove hydrogen sulfide without forming by-products that affect the quality and costs of natural gas processing, transport and distribution is of great importance. In this context, the evaluation of the kinetics of H2S removal is a valuable procedure for the treatment of natural gas and disposal of the byproducts generated by the process. This evaluation was made in an absorption column packed with Raschig ring, where natural gas with H2S passes through a stagnant solution, being the contaminant absorbed by it. The content of H2S in natural gas in column output was monitored by an H2S analyzer. The comparison between the obtained curves and the study of the involved reactions have not only allowed to determine the efficiency and mass transfer controlling step of the involved processes but also make possible to effect a more detailed kinetic study and evaluate the commercial potential of each reagent
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During natural gas processing, water removal is considered as a fundamental step in that combination of hydrocarbons and water favors the formation of hydrates. The gas produced in the Potiguar Basin (Brazil) presents high water content (approximately 15000 ppm) and its dehydration is achieved via absorption and adsorption operations. This process is carried out at the Gas Treatment Unit (GTU) in Guamaré (GMR), in the State of Rio Grande do Norte. However, it is a costly process, which does not provide satisfactory results when water contents as low as 0.5 ppm are required as the exit of the GTU. In view of this, microemulsions research is regarded as an alternative to natural gas dehydration activities. Microemulsions can be used as desiccant fluids because of their unique proprieties, namely solubilization enhancement, reduction in interfacial tensions and large interfacial area between continuous and dispersed phases. These are actually important parameters to ensure the efficiency of an absorption column. In this work, the formulation of the desiccant fluid was determined via phases diagram construction, employing there nonionic surfactants (RDG 60, UNTL L60 and AMD 60) and a nonpolar fluid provided by Petrobras GMR (Brazil) typically comprising low-molecular weight liquid hydrocarbons ( a solvent commonly know as aguarrás ). From the array of phases diagrams built, four representative formulations have been selected for providing better results: 30% RDG 60-70% aguarrás; 15% RDG 60-15% AMD 60-70% aguarrás, 30% UNTL L60-70% aguarrás, 15% UNTL L60-15% AMD 60-70% aguarrás. Since commercial natural gas is already processed, and therefore dehydrated, it was necessary to moister some sample prior to all assays. It was then allowed to cool down to 13ºC and interacted with wet 8-12 mesh 4A molecular sieve, thus enabling the generation of gas samples with water content (approximately 15000 ppm). The determination of the equilibrium curves was performed based on the dynamic method, which stagnated liquid phase and gas phase at a flow rate of 200 mL min-1. The hydrodynamic study was done with the aim of established the pressure drop and dynamic liquid hold-up. This investigation allowed are to set the working flow rates at 840 mL min-1 for the gas phase and 600 mLmin-1 for the liquid phase. The mass transfer study indicated that the system formed by UNTL L60- turpentine-natural gas the highest value of NUT
Resumo:
Natural gas, although basically composed by light hydrocarbons, also presents contaminant gases in its composition, such as CO2 (carbon dioxide) and H2S (hydrogen sulfide). The H2S, which commonly occurs in oil and gas exploration and production activities, causes damages in oil and natural gas pipelines. Consequently, the removal of hydrogen sulfide gas will result in an important reduction in operating costs. Also, it is essential to consider the better quality of the oil to be processed in the refinery, thus resulting in benefits in economic, environmental and social areas. All this facts demonstrate the need for the development and improvement in hydrogen sulfide scavengers. Currently, the oil industry uses several processes for hydrogen sulfide removal from natural gas. However, these processes produce amine derivatives which can cause damage in distillation towers, can cause clogging of pipelines by formation of insoluble precipitates, and also produce residues with great environmental impact. Therefore, it is of great importance the obtaining of a stable system, in inorganic or organic reaction media, able to remove hydrogen sulfide without formation of by-products that can affect the quality and cost of natural gas processing, transport, and distribution steps. Seeking the study, evaluation and modeling of mass transfer and kinetics of hydrogen removal, in this study it was used an absorption column packed with Raschig rings, where the natural gas, with H2S as contaminant, passed through an aqueous solution of inorganic compounds as stagnant liquid, being this contaminant gas absorbed by the liquid phase. This absorption column was coupled with a H2S detection system, with interface with a computer. The data and the model equations were solved by the least squares method, modified by Levemberg-Marquardt. In this study, in addition to the water, it were used the following solutions: sodium hydroxide, potassium permanganate, ferric chloride, copper sulfate, zinc chloride, potassium chromate, and manganese sulfate, all at low concentrations (»10 ppm). These solutions were used looking for the evaluation of the interference between absorption physical and chemical parameters, or even to get a better mass transfer coefficient, as in mixing reactors and absorption columns operating in counterflow. In this context, the evaluation of H2S removal arises as a valuable procedure for the treatment of natural gas and destination of process by-products. The study of the obtained absorption curves makes possible to determine the mass transfer predominant stage in the involved processes, the mass transfer volumetric coefficients, and the equilibrium concentrations. It was also performed a kinetic study. The obtained results showed that the H2S removal kinetics is greater for NaOH. Considering that the study was performed at low concentrations of chemical reagents, it was possible to check the effect of secondary reactions in the other chemicals, especially in the case of KMnO4, which shows that your by-product, MnO2, acts in H2S absorption process. In addition, CuSO4 and FeCl3 also demonstrated to have good efficiency in H2S removal
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This paper presents models that can be used in the design of microstrip antennas for mobile communications. The antennas can be triangular or rectangular. The presented models are compared with deterministic and empirical models based on artificial neural networks (ANN) presented in the literature. The models are based on Perceptron Multilayer (PML) and Radial Basis Function (RBF) ANN. RBF based models presented the best results. Also, the models can be embedded in CAD systems, in order to design microstrip antennas for mobile communications.
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This paper describes the UNESP robotic team in the medical trash collector task, proposed on the 5 rd IEEE Latin American Robots Competition in the LEGO category. We present our understanding of the task and discuss the proposed solution, focusing on the mechanical and computational issues of the robots. The mechanics is based on rigid body capability of transforming rotational into curvilinear movement. With respect to the computational control, the system is modeled as a reactive system with sequential transition of behaviors. A state-machine is proposed to allow this transition, and the synchronization of robotic states is guaranteed by the communication system. The proposed approach has shown itself capable of dealing with the high difficulty degree of this cooperative task. ©2006 IEEE.
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The need for the representation of both semantics and common sense and its organization in a lexical database or knowledge base has motivated the development of large projects, such as Wordnets, CYC and Mikrokosmos. Besides the generic bases, another approach is the construction of ontologies for specific domains. Among the advantages of such approach there is the possibility of a greater and more detailed coverage of a specific domain and its terminology. Domain ontologies are important resources in several tasks related to the language processing, especially in those related to information retrieval and extraction in textual bases. Information retrieval or even question and answer systems can benefit from the domain knowledge represented in an ontology. Besides embracing the terminology of the field, the ontology makes the relationships among the terms explicit. Copyright 2007 ACM.
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This paper discusses two pitch detection algorithms (PDA) for simple audio signals which are based on zero-cross rate (ZCR) and autocorrelation function (ACF). As it is well known, pitch detection methods based on ZCR and ACF are widely used in signal processing. This work shows some features and problems in using these methods, as well as some improvements developed to increase their performance. © 2008 IEEE.
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A comparative evaluation was made of the use of natural language versus two specialized indexing languages, aiming to demonstrate the influence of the availability of indexing languages on the functioning of information retrieval systems. The study was conducted within the ambit of the construction of search strategies by subject in online university library catalogs. The precision ratio was calculated to determine the accuracy of each indexing language in subjectbased information retrieval. From the comparative evaluation of the use of indexing languages, it was concluded that the term specificity required by the user during retrieval was more satisfactory when the query was made through controlled languages, whose availability and simplicity is also an indispensable requisite.