54 resultados para Clustering evaluation


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This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

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Micro-generation is the small scale production of heat and/or electricity from a low carbon source and can be a powerful driver for carbon reduction, behavior change, security of supply and economic value. The energy conversion technologies can include photovoltaic panels, micro combined heat and power, micro wind, heat pumps, solar thermal systems, fuel cells and micro hydro schemes. In this paper, a small research of the availability of the conversion apparatus and the prices for the micro wind turbines and photovoltaic systems is made and a comparison between these two technologies is performed in terms of the availability of the resource and costs. An analysis of the new legal framework published in Portugal is done to realize if the incentives to individualspsila investment in sustainable and local energy production is worth for their point of view. An economic evaluation for these alternatives, accounting with the governmentpsilas incentives should lead, in most cases, into attractive return rates for the investment. Apart from the attractiveness of the investment there are though other aspects that should be taken into account and those are the benefits that these choices have to us all. The idea is that micro-generation will not only make a significant direct contribution to carbon reduction targets, it will also trigger a multiplier effect in behavior change by engaging hearts and minds, and providing more efficient use of energy by householders. The diversified profile of power generation by micro-generators, both in terms of location and timing, should reduce the impact of intermittency or plant failures with significant gains for security of supply.

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Introduction: The purpose of this review is to gather and analyse current research publications to evaluate Sinogram-Affirmed Iterative Reconstruction (SAFIRE). The aim of this review is to investigate whether this algorithm is capable of reducing the dose delivered during CT imaging while maintaining image quality. Recent research shows that children have a greater risk per unit dose due to increased radiosensitivity and longer life expectancies, which means it is particularly important to reduce the radiation dose received by children. Discussion: Recent publications suggest that SAFIRE is capable of reducing image noise in CT images, thereby enabling the potential to reduce dose. Some publications suggest a decrease in dose, by up to 64% compared to filtered back projection, can be accomplished without a change in image quality. However, literature suggests that using a higher SAFIRE strength may alter the image texture, creating an overly ‘smoothed’ image that lacks contrast. Some literature reports SAFIRE gives decreased low contrast detectability as well as spatial resolution. Publications tend to agree that SAFIRE strength three is optimal for an acceptable level of visual image quality, but more research is required. The importance of creating a balance between dose reduction and image quality is stressed. In this literature review most of the publications were completed using adults or phantoms, and a distinct lack of literature for paediatric patients is noted. Conclusion: It is necessary to find an optimal way to balance dose reduction and image quality. More research relating to SAFIRE and paediatric patients is required to fully investigate dose reduction potential in this population, for a range of different SAFIRE strengths.

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Considering that recent european high-speed railway system has a traction power system of kV 50 Hz, which causes electromagnetic emission for the outside world, it is important to dimension the railway system emissions, using a frequency/distance dependent propagation model. This paper presents an enhanced theoretical model for VLF to UHF propagation, railway system oriented. It introduces the near field approach (crucial in low frequency propagation) and also considers the source characteristics and type of measuring antenna. Simulations are presented, and comparisons are set with earlier far field models. Using the developed model, a real case study was performed in partnership with Refer Telecom (portuguese telecom operator for railways). The new propagation model was used in order to predict the future high-speed railway electromagnetic emissions in the Lisbon north track. The results show the model's prediction capabilities and also its applicability to realistic scenarios.

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Radio frequency (RF) energy harvesting is an emerging technology that will enable to drive the next generation of wireless sensor networks (WSNs) without the need of using batteries. In this paper, we present RF energy harvesting circuits specifically developed for GSM bands (900/1800) and a wearable dual-band antenna suitable for possible implementation within clothes for body worn applications. Besides, we address the development and experimental characterization of three different prototypes of a five-stage Dickson voltage multiplier (with match impedance circuit) responsible for harvesting the RF energy. Different printed circuit board (PCB) fabrication techniques to produce the prototypes result in different values of conversion efficiency. Therefore, we conclude that if the PCB fabrication is achieved by means of a rigorous control in the photo-positive method and chemical bath procedure applied to the PCB it allows for attaining better values for the conversion efficiency. All three prototypes (1, 2 and 3) can power supply the IRIS sensor node for RF received powers of -4 dBm, -6 dBm and -5 dBm, and conversion efficiencies of 20, 32 and 26%, respectively. © 2014 IEEE.

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Biosignals analysis has become widespread, upstaging their typical use in clinical settings. Electrocardiography (ECG) plays a central role in patient monitoring as a diagnosis tool in today's medicine and as an emerging biometric trait. In this paper we adopt a consensus clustering approach for the unsupervised analysis of an ECG-based biometric records. This type of analysis highlights natural groups within the population under investigation, which can be correlated with ground truth information in order to gain more insights about the data. Preliminary results are promising, for meaningful clusters are extracted from the population under analysis. © 2014 EURASIP.

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Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

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Applications involving biosignals, such as Electrocardiography (ECG), are becoming more pervasive with the extension towards non-intrusive scenarios helping targeting ambulatory healthcare monitoring, emotion assessment, among many others. In this study we introduce a new type of silver/silver chloride (Ag/AgCl) electrodes based on a paper substrate and produced using an inkjet printing technique. This type of electrodes can increase the potential applications of biosignal acquisition technologies for everyday life use, given that there are several advantages, such as cost reduction and easier recycling, resultant from the approach explored in our work. We performed a comparison study to assess the quality of this new electrode type, in which ECG data was collected with three types of Ag/AgCl electrodes: i) gelled; ii) dry iii) paper-based inkjet printed. We also compared the performance of each electrode when acquired using a professional-grade gold standard device, and a low cost platform. Experimental results showed that data acquired using our proposed inkjet printed electrode is highly correlated with data obtained through conventional electrodes. Moreover, the electrodes are robust to high-end and low-end data acquisition devices. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

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This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

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The disturbing emergence of multidrug-resistant strains of Mycobacterium tuberculosis (Mtb) has been driving the scientific community to urgently search for new and efficient antitubercular drugs. Despite the various drugs currently under evaluation, isoniazid is still the key and most effective component in all multi-therapeutic regimens recommended by the WHO. This paper describes the QSAR-oriented design, synthesis and in vitro antitubercular activity of several potent isoniazid derivatives (isonicotinoyl hydrazones and isonicotinoyl hydrazides) against H37Rv and two resistant Mtb strains. QSAR studies entailed RFs and ASNNs classification models, as well as MLR models. Strict validation procedures were used to guarantee the models' robustness and predictive ability. Lipophilicity was shown not to be relevant to explain the activity of these derivatives, whereas shorter N-N distances and lengthy substituents lead to more active compounds. Compounds I, 2, 4, 5 and 6, showed measured activities against H37Rv higher than INH (i.e., MIC <= 0.28 mu M), while compound 9 exhibited a six fold decrease in MIC against the katG (S315T) mutated strain, by comparison with INH (Le., 6.9 vs. 43.8 mu M). All compounds were ineffective against H37Rv(INH) (Delta katG), a strain with a full deletion of the katG gene, thus corroborating the importance of KatG in the activation of INH-based compounds. The most potent compounds were also shown not to be cytotoxic up to a concentration 500 times higher than MIC. (C) 2014 Elsevier Masson SAS. All rights reserved.

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Hierarchical SAPO-11 was synthesized using a commercial Merck carbon as template. Oxidant acid treatments were performed on the carbon matrix in order to investigate its influence on the properties of SAPO-11. Structural, textural and acidic properties of the different materials were evaluated by XRD, SEM, N-2 adsorption, pyridine adsorption followed by IR spectroscopy and thermal analyses. The catalytic behavior of the materials (with 0.5 wt.% Pt, introduced by mechanic mixture with Pt/Al2O3), were studied in the hydroisomerization of n-decane. The hierarchical samples showed higher yields in monobranched isomers than typical microporous SAPO-11, as a direct consequence of the modification on both porosity and acidity, the later one being the most predominant. (C) 2014 Elsevier B.V. All rights reserved.

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In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion. © 2014 Springer-Verlag Berlin Heidelberg.

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Outlining the best strategies for seismic risk mitigation requires that both benefits and costs of retrofitting are known in advance. The assessment of the vulnerability of building typologies is a first step of a more extensive effort, concerning the analysis of the viability of seismic risk mitigation and taking into account retrofitting costs. The methodology adopted to obtain the seismic vulnerability of some classes of residential buildings existing in mainland Portugal is presented. This methodology is based on a structural analysis of individual buildings belonging to the same typology. An application example is presented to illustrate the methodology. Fragility curves of “boxed” building typology are also presented and broken down into three height classes: low rise, medium-rise and high-rise. These curves are based on average capacity spectra derived from several individual buildings belonging to the same typology.

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The main goals of the present work are the evaluation of the influence of several variables and test parameters on the melt flow index (MFI) of thermoplastics, and the determination of the uncertainty associated with the measurements. To evaluate the influence of test parameters on the measurement of MFI the design of experiments (DOE) approach has been used. The uncertainty has been calculated using a "bottom-up" approach given in the "Guide to the Expression of the Uncertainty of Measurement" (GUM). Since an analytical expression relating the output response (MFI) with input parameters does not exist, it has been necessary to build mathematical models by adjusting the experimental observations of the response variable in accordance with each input parameter. Subsequently, the determination of the uncertainty associated with the measurement of MFI has been performed by applying the law of propagation of uncertainty to the values of uncertainty of the input parameters. Finally, the activation energy (Ea) of the melt flow at around 200 degrees C and the respective uncertainty have also been determined.

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Additional apple juice extraction with pulsed electric field pretreated apple cubes towards control samples is evaluated. Monopolar and bipolar shaped pulses are compared and their effect is studied with variation of electric field, pulse width and number of pulses. Variation of electric field strength is ranged from 100 V/cm to 1300 V/cm, pulse width from 20 mu s to 300 mu s and number of pulses from 10 to 200, at frequency of 200Hz. Two pulse trains separated by 1 second are applied to all samples. Bipolar pulses showed higher apple juice yields with all studied parameters. Calculation of specific energies consumed was assessed and a threshold where higher energy inputs do not increase juice yield is found for a number of used parameters. Qualitative parameters of total soluble matter (Brix) and absorbance at 390 nm wavelength were determined for each sample and results show that no substantial differences are found for PEF pre-treated and control samples.