61 resultados para Pattern Informatics Method


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The local fractional Poisson equations in two independent variables that appear in mathematical physics involving the local fractional derivatives are investigated in this paper. The approximate solutions with the nondifferentiable functions are obtained by using the local fractional variational iteration method.

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This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

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Performance evaluation increasingly assumes a more important role in any organizational environment. In the transport area, the drivers are the company’s image and for this reason it is important to develop and increase their performance and commitment to the company goals. This evaluation can be used to motivate driver to improve their performance and to discover training needs. This work aims to create a performance appraisal evaluation model of the drivers based on the multi-criteria decision aid methodology. The MMASSI (Multicriteria Methodology to Support Selection of Information Systems) methodology was adapted by using a template supporting the evaluation according to the freight transportation company in study. The evaluation process involved all drivers (collaborators being evaluated), their supervisors and the company management. The final output is a ranking of the drivers, based on their performance, for each one of the scenarios used.

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The choice of an information systems is a critical factor of success in an organization's performance, since, by involving multiple decision-makers, with often conflicting objectives, several alternatives with aggressive marketing, makes it particularly complex by the scope of a consensus. The main objective of this work is to make the analysis and selection of a information system to support the school management, pedagogical and administrative components, using a multicriteria decision aid system – MMASSITI – Multicriteria Method- ology to Support the Selection of Information Systems/Information Technologies – integrates a multicriteria model that seeks to provide a systematic approach in the process of choice of Information Systems, able to produce sustained recommendations concerning the decision scope. Its application to a case study has identi- fied the relevant factors in the selection process of school educational and management information system and get a solution that allows the decision maker’ to compare the quality of the various alternatives.

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In this study, we sought to assess the applicability of GC–MS/MS for the identification and quantification of 36 pesticides in strawberry from integrated pest management (IPM) and organic farming (OF). Citrate versions of QuEChERS (quick, easy, cheap, effective, rugged and safe) using dispersive solid-phase extraction (d-SPE) and disposable pipette extraction (DPX) for cleanup were compared for pesticide extraction. For cleanup, a combination of MgSO4, primary secondary amine and C18 was used for both the versions. Significant differences were observed in recovery results between the two sample preparation versions (DPX and d-SPE). Overall, 86% of the pesticides achieved recoveries (three spiking levels 10, 50 and 200 µg/kg) in the range of 70–120%, with <13% RSD. The matrix effects were also evaluated in both the versions and in strawberries from different crop types. Although not evidencing significant differences between the two methodologies were observed, however, the DPX cleanup proved to be a faster technique and easy to execute. The results indicate that QuEChERS with d-SPE and DPX and GC–MS/MS analysis achieved reliable quantification and identification of 36 pesticide residues in strawberries from OF and IPM.

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Na atualidade, existe uma quantidade de dados criados diariamente que ultrapassam em muito as mais otimistas espectativas estabelecidas na década anterior. Estes dados têm origens bastante diversas e apresentam-se sobre várias formas. Este novo conceito que dá pelo nome de Big Data está a colocar novos e rebuscados desafios ao seu armazenamento, tratamento e manipulação. Os tradicionais sistemas de armazenamento não se apresentam como a solução indicada para este problema. Estes desafios são alguns dos mais analisados e dissertados temas informáticos do momento. Várias tecnologias têm emergido com esta nova era, das quais se salienta um novo paradigma de armazenamento, o movimento NoSQL. Esta nova filosofia de armazenamento visa responder às necessidades de armazenamento e processamento destes volumosos e heterogéneos dados. Os armazéns de dados são um dos componentes mais importantes do âmbito Business Intelligence e são, maioritariamente, utilizados como uma ferramenta de apoio aos processos de tomada decisão, levados a cabo no dia-a-dia de uma organização. A sua componente histórica implica que grandes volumes de dados sejam armazenados, tratados e analisados tendo por base os seus repositórios. Algumas organizações começam a ter problemas para gerir e armazenar estes grandes volumes de informação. Esse facto deve-se, em grande parte, à estrutura de armazenamento que lhes serve de base. Os sistemas de gestão de bases de dados relacionais são, há algumas décadas, considerados como o método primordial de armazenamento de informação num armazém de dados. De facto, estes sistemas começam a não se mostrar capazes de armazenar e gerir os dados operacionais das organizações, sendo consequentemente cada vez menos recomendada a sua utilização em armazéns de dados. É intrinsecamente interessante o pensamento de que as bases de dados relacionais começam a perder a luta contra o volume de dados, numa altura em que um novo paradigma de armazenamento surge, exatamente com o intuito de dominar o grande volume inerente aos dados Big Data. Ainda é mais interessante o pensamento de que, possivelmente, estes novos sistemas NoSQL podem trazer vantagens para o mundo dos armazéns de dados. Assim, neste trabalho de mestrado, irá ser estudada a viabilidade e as implicações da adoção de bases de dados NoSQL, no contexto de armazéns de dados, em comparação com a abordagem tradicional, implementada sobre sistemas relacionais. Para alcançar esta tarefa, vários estudos foram operados tendo por base o sistema relacional SQL Server 2014 e os sistemas NoSQL, MongoDB e Cassandra. Várias etapas do processo de desenho e implementação de um armazém de dados foram comparadas entre os três sistemas, sendo que três armazéns de dados distintos foram criados tendo por base cada um dos sistemas. Toda a investigação realizada neste trabalho culmina no confronto da performance de consultas, realizadas nos três sistemas.

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Disaster management is one of the most relevant application fields of wireless sensor networks. In this application, the role of the sensor network usually consists of obtaining a representation or a model of a physical phenomenon spreading through the affected area. In this work we focus on forest firefighting operations, proposing three fully distributed ways for approximating the actual shape of the fire. In the simplest approach, a circular burnt area is assumed around each node that has detected the fire and the union of these circles gives the overall fire’s shape. However, as this approach makes an intensive use of the wireless sensor network resources, we have proposed to incorporate two in-network aggregation techniques, which do not require considering the complete set of fire detections. The first technique models the fire by means of a complex shape composed of multiple convex hulls representing different burning areas, while the second technique uses a set of arbitrary polygons. Performance evaluation of realistic fire models on computer simulations reveals that the method based on arbitrary polygons obtains an improvement of 20% in terms of accuracy of the fire shape approximation, reducing the overhead in-network resources to 10% in the best case.

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This work proposes a novel approach for a suitable orientation of antibodies (Ab) on an immunosensing platform, applied here to the determination of 8-hydroxy-2′-deoxyguanosine (8OHdG), a biomarker of oxidative stress that has been associated to chronic diseases, such as cancer. The anti-8OHdG was bound to an amine modified gold support through its Fc region after activation of its carboxylic functions. Non-oriented approaches of Ab binding to the platform were tested in parallel, in order to show that the presented methodology favored Ab/Ag affinity and immunodetection of the antigen. The immunosensor design was evaluated by quartz-crystal microbalance with dissipation, atomic force microscopy, electrochemical impedance spectroscopy (EIS) and square-wave voltammetry. EIS was also a suitable technique to follow the analytical behavior of the device against 8OHdG. The affinity binding between 8OHdG and the antibody immobilized in the gold modified platform increased the charge transfer resistance across the electrochemical set-up. The observed behavior was linear from 0.02 to 7.0 ng/mL of 8OHdG concentrations. The interference from glucose, urea and creatinine was found negligible. An attempt of application to synthetic samples was also successfully conducted. Overall, the presented approach enabled the production of suitably oriented Abs over a gold platform by means of a much simpler process than other oriented-Ab binding approaches described in the literature, as far as we know, and was successful in terms of analytical features and sample application.

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The total antioxidant capacity (TAC) of 28 flavoured water samples was assessed by ferric reducing antioxidant potential (FRAP), oxygen radical absorbance capacity (ORAC), trolox equivalent antioxidant capacity (TEAC) and total reactive antioxidant potential (TRAP) methods. It was observed that flavoured waters had higher antioxidant activity than the corresponding natural ones. The observed differences were attributed to flavours, juice and vitamins. Generally, higher TAC contents were obtained on lemon waters and lower values on guava and raspberry flavoured waters. Lower and higher TACs were obtained by TRAP and ORAC method, respectively. Statistical analysis suggested that vitamins and flavours increased the antioxidant content of the commercial waters.

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Sulfadiazine is an antibiotic of the sulfonamide group and is used as a veterinary drug in fish farming. Monitoring it in the tanks is fundamental to control the applied doses and avoid environmental dissemination. Pursuing this goal, we included a novel potentiometric design in a flow-injection assembly. The electrode body was a stainless steel needle veterinary syringe of 0.8-mm inner diameter. A selective membrane of PVC acted as a sensory surface. Its composition, the length of the electrode, and other flow variables were optimized. The best performance was obtained for sensors of 1.5-cm length and a membrane composition of 33% PVC, 66% onitrophenyloctyl ether, 1% ion exchanger, and a small amount of a cationic additive. It exhibited Nernstian slopes of 61.0 mV decade-1 down to 1.0×10-5 mol L-1, with a limit of detection of 3.1×10-6 mol L-1 in flowing media. All necessary pH/ionic strength adjustments were performed online by merging the sample plug with a buffer carrier of 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid, pH 4.9. The sensor exhibited the advantages of a fast response time (less than 15 s), long operational lifetime (60 days), and good selectivity for chloride, nitrite, acetate, tartrate, citrate, and ascorbate. The flow setup was successfully applied to the analysis of aquaculture waters. The analytical results were validated against those obtained with liquid chromatography–tandem mass spectrometry procedures. The sampling rate was about 84 samples per hour and recoveries ranged from 95.9 to 106.9%.

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The local fractional Poisson equations in two independent variables that appear in mathematical physics involving the local fractional derivatives are investigated in this paper. The approximate solutions with the nondifferentiable functions are obtained by using the local fractional variational iteration method.

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This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

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This work presents an automatic calibration method for a vision based external underwater ground-truth positioning system. These systems are a relevant tool in benchmarking and assessing the quality of research in underwater robotics applications. A stereo vision system can in suitable environments such as test tanks or in clear water conditions provide accurate position with low cost and flexible operation. In this work we present a two step extrinsic camera parameter calibration procedure in order to reduce the setup time and provide accurate results. The proposed method uses a planar homography decomposition in order to determine the relative camera poses and the determination of vanishing points of detected lines in the image to obtain the global pose of the stereo rig in the reference frame. This method was applied to our external vision based ground-truth at the INESC TEC/Robotics test tank. Results are presented in comparison with an precise calibration performed using points obtained from an accurate 3D LIDAR modelling of the environment.

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In this study a citrate-buffered version of QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method for determination of 14 organochlorine pesticides (OCPs) residues in tamarind peel, fruit and commercial pulp was optimized using gas chromatography (GC) coupled with electron-capture detector (ECD) and confirmation by GC tandem mass spectrometry (GC–MS/MS). Five procedures were tested based on the original QuEChERS method. The best one was achieved with increased time in ultrasonic bath. For the extract clean-up, primary secondary amine (PSA), octadecyl-bonded silica (C18) and magnesium sulphate (MgSO4) were used as sorbents for tamarind fruit and commercial pulp and for peel was also added graphitized carbon black (GCB). The samples mass was optimized according to the best recoveries (1.0 g for peel and fruit; 0.5 g for pulp). The method results showed the matrix-matched calibration curve linearity was r2 > 0.99 for all target analytes in all samples. The overall average recoveries (spiked at 20, 40 and 60 μg kg−1) have been considered satisfactory presenting values between 70 and 115% with RSD of 2–15 % (n = 3) for all analytes, with the exception of HCB (in peel sample). The ranges of limits of detection (LOD) and quantification (LOQ) for OCPs were for peel (LOD: 8.0–21 μg kg−1; LOQ: 27–98 μg kg−1); for fruit (LOD: 4–10 μg kg−1; LOQ: 15–49 μg kg−1) and for commercial pulp (LOD: 2–5 μg kg−1; LOQ: 7–27 μg kg−1). The method was successfully applied in tamarind samples being considered a rapid, sensitive and reliable procedure.