Low Complexity Intra Mode Selection for Efficient Distributed Video Coding

Motion compensated frame interpolation (MCFI) is one of the most efficient solutions to generate side information (SI) in the context of distributed video coding. However, it creates SI with rather significant motion compensated errors for some frame regions while rather small for some other regions depending on the video content. In this paper, a low complexity Infra mode selection algorithm is proposed to select the most 'critical' blocks in the WZ frame and help the decoder with some reliable data for those blocks. For each block, the novel coding mode selection algorithm estimates the encoding rate for the Intra based and WZ coding modes and determines the best coding mode while maintaining a low encoder complexity. The proposed solution is evaluated in terms of rate-distortion performance with improvements up to 1.2 dB regarding a WZ coding mode only solution.

Application of GIS-based multi-criteria analysis for site selection of aquifer recharge with reclaimed water

Reclaimed water from small wastewater treatment facilities in the rural areas of the Beira Interior region (Portugal) may constitute an alternative water source for aquifer recharge. A 21-month monitoring period in a constructed wetland treatment system has shown that 21,500 m(3) year(-1) of treated wastewater (reclaimed water) could be used for aquifer recharge. A GIS-based multi-criteria analysis was performed, combining ten thematic maps and economic, environmental and technical criteria, in order to produce a suitability map for the location of sites for reclaimed water infiltration. The areas chosen for aquifer recharge with infiltration basins are mainly composed of anthrosol with more than 1 m deep and fine sand texture, which allows an average infiltration velocity of up to 1 m d(-1). These characteristics will provide a final polishing treatment of the reclaimed water after infiltration (soil aquifer treatment (SAT)), suitable for the removal of the residual load (trace organics, nutrients, heavy metals and pathogens). The risk of groundwater contamination is low since the water table in the anthrosol areas ranges from 10 m to 50 m. Oil the other hand, these depths allow a guaranteed unsaturated area suitable for SAT. An area of 13,944 ha was selected for study, but only 1607 ha are suitable for reclaimed water infiltration. Approximately 1280 m(2) were considered enough to set up 4 infiltration basins to work in flooding and drying cycles.

Fungal and microbial volatile organic compounds exposure assessment in a waste sorting plant

In the management of solid waste, pollutants over a wide range are released with different routes of exposure for workers. The potential for synergism among the pollutants raises concerns about potential adverse health effects, and there are still many uncertainties involved in exposure assessment. In this study, conventional (culture-based) and molecular real-time polymerase chain reaction (RTPCR) methodologies were used to assess fungal air contamination in a waste-sorting plant which focused on the presence of three potential pathogenic/toxigenic fungal species: Aspergillus flavus, A. fumigatus, and Stachybotrys chartarum. In addition, microbial volatile organic compounds (MVOC) were measured by photoionization detection. For all analysis, samplings were performed at five different workstations inside the facilities and also outdoors as a reference. Penicillium sp. were the most common species found at all plant locations. Pathogenic/toxigenic species (A. fumigatus and S. chartarum) were detected at two different workstations by RTPCR but not by culture-based techniques. MVOC concentration indoors ranged between 0 and 8.9 ppm (average 5.3 ± 3.16 ppm). Our results illustrated the advantage of combining both conventional and molecular methodologies in fungal exposure assessment. Together with MVOC analyses in indoor air, data obtained allow for a more precise evaluation of potential health risks associated with bioaerosol exposure. Consequently, with this knowledge, strategies may be developed for effective protection of the workers.

Nanofiltration for the treatment of coke plant ammoniacal wastewaters

This work addresses the treatment by nanofiltration (NF) of solutions containing NaCN and NH(4)Cl at various pH values. The NF experiments are carried out in a Lab-Unit equipped with NF-270 membranes for model solutions that are surrogates of industrial ammoniacal wastewaters generated in the coke-making processes. The applied pressure is 30 bar. The main objective is the separation of the compounds NaCN and NH(4)Cl and the optimization of this separation as a function of the pH. Membrane performance is highly dependent on solution composition and characteristics, namely on the pH. In fact, the rejection coefficients for the binary model solution containing sodium cyanide are always higher than the rejections coefficients for the ammonium chloride model solution. For ternary solutions (cyanide/ammonium/water) it was observed that for pH values lower than 9 the rejection coefficients to ammonium are well above the ones observed for the cyanides, but for pH values higher than 9.5 there is a drastic decrease in the ammonium rejection coefficients with the increase of the pH. These results take into account the changes that occur in solution, namely, the solute species that are predominant, with the increase of the pH. The fluxes of the model solutions decreased with increased pH. (C) 2010 Elsevier B.V. All rights reserved.

Exposure to volatile organic compounds in a composting plant

Some previous studies have suggested that some of the volatile organic compounds (VOCs) found in composting plants may have a toxic effect that can influence, besides surroundings populations, workers from the composting plants. Impact of waste management to the environment and workers is already recognised as an environment and occupational health concerns. Several studies regarding the VOCs and bioaerosols emissions from composting have been conducted all over Europe and also in Asia. However, in Portugal the studies developed are scarce and normally VOCs are not studied and recognized as a risk factor present in this occupational setting. Consudering this, a study was developed in a Portuguese composting plant aiming to clarify if there was VOCs presence in the workplaces.

Aspergillus genera fungal contamination in a Portuguese composting plant

Fungal contamination in composting facilities has been associated with increased respiratory and skin pathologies among compost workers. In this study we aim to characterize the fungal contamination caused by Aspergillus genera within a totally indoor composting plant located in Portugal. Air samples of 50L were collected from 6 sampling sites through an impaction method. Surfaces samples were collected by swabbing the surfaces of the same indoor sites. Pre-treatment and waste screw were the sampling sites of the analyzed composting plant with the highest Aspergillus load in the air. Globally, the genus Aspergillus presented the highest prevalence both in the air from (90.6%), and surfaces from the same sampling sites (60.8%). The results obtained in this study claim the attention to the need of further research regarding the fungal contamination dur to Aspergillus genus in composting plants.

Occupational exposure to particulate matter and fungi in a composting plant: case study in Portugal

The handling of waste can be responsible for occupational exposure to particles and fungi. The aim of this study was to characterize exposure to particles and fungi in a composting plant. Measurements of particulate matter were performed using portable direct-reading equipment. Air samples of 50L were collected through an impaction method with a flow rate of 140L/min onto malt extract agar supplemented with chloramphenicol (0.05%). Surfaces samples were also collected. All the samples were incubated at 27ºC for 5 to 7 days. Particulate matter data showed higher contamination for PM, and PM10 sizes. Aspergillus genus presents the highest air prevalence (90.6%). Aspergillus niger (32.6%), A. fumigatus (26.5%) and A. flavus (16.3%) were the most prevalent fungi in air sampling, and Mucor sp. (39.2%), Aspergillus niger (30.9%) and A. fumigatus (28.7%) were the most found in surfaces. the results obtained claim the attention to the need of further research.

Complementarity of conventional and molecular methods in the assessment of fungal contamination caused by Aspergillus fumigatus complex in one Portuguese composting plant

The handling of waste and compost that occurs frequently in composting plants (compost turning, shredding, and screening) has been shown to be responsible for the release of dust and air borne microorganisms and their compounds in the air. Thermophilic fungi, such as A. fumigatus, have been reported and this kind of contamination in composting facilities has been associated with increased respiratory symptoms among compost workers. This study intended to characterize fungal contamination in a totally indoor composting plant located in Portugal. Besides conventional methods, molecular biology was also applied to overcome eventual limitations.

How to mimic the shapes of plant tendrils on the nano and microscale: spirals and helices of electrospun liquid crystalline cellulose derivatives

We show that suspended nano and microfibres electrospun from liquid crystalline cellulosic solutions will curl into spirals if they are supported at just one end, or, if they are supported at both ends, will twist into a helix of one handedness over half of its length and of the opposite handedness over the other half, the two halves being connected by a short straight section. This latter phenomenon, known as perversion, is a consequence of the intrinsic curvature of the fibres and of a topological conservation law. Furthermore, agreement between theory and experiment can only be achieved if account is taken of the intrinsic torsion of the fibres. Precisely the same behaviour is known to be exhibited by the tendrils of climbing plants such as Passiflora edulis, albeit on a lengthscale of millimetres, i.e., three to four orders of magnitude larger than in our fibres. This suggests that the same basic, coarse-grained physical model is applicable across a range of lengthscales.

Exposure to volatile organic compounds, particulate matter and fungi in a composting plant

Composting is an important process of solid waste management and it can be used for treatment of a variety of different wastes (green waste, household waste, sewage sludge and more). This process aims to: 1. Reduce the volumes of waste and; 2. Create a valuable product which can be recycled as a soil amendment in agriculture and gardening. A natural self-heating process involving the biological degradation of organic matter under aerobic conditions. The handling of waste and compost is responsible for the release of airborne microorganisms and their compounds in the air. Possible contaminants: a) Dust; b) Mesophilic and thermophilic microorganisms; c) Volatile organic compounds; d) Endotoxins and mycotoxins…. Aim: assess exposure/contamination to: a) Volatile organic compounds (VOCs); b) Particulate matter (PM); c) Fungi. In a composting plant located in Lisbon. An additional goal was to identify the workplace with higher level of contamination. In a totally indoor composting plant. The composting operations consisted: 1º Waste already sorted is unloaded in a reception area; 2º Pretreatment - remove undesirable materials from the process (glass, rocks, plastics, metals…); 3º Anaerobic digestion; 4º Dehydration; 5º Open composting with forced aeration. All the process takes thirteen weeks.

Study of the production of polyesters for polyurethanes at pilot plant scale

Dissertação para obtenção do grau de Mestre em Engenharia Química

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

Projecto e concepção de instalação frigorífica a NH3, para uma unidade de congelação de frangos em contínuo, na Venezuela

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

ECG Biometrics: A Template Selection Approach

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.

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.