Estimation of pollutant partition in sandy soils with different water contents

The objectives of this work were: (1) to identify an isotherm model to relate the contaminant contents in the gas phase with those in the solid and non-aqueous liquid phases; (2) to develop a methodology for the estimation of the contaminant distribution in the different phases of the soil; and (3) to evaluate the influence of soil water content on the contaminant distribution in soil. For sandy soils with negligible contents of clay and natural organic matter, contaminated with benzene, toluene, ethylbenzene, xylene, trichloroethylene (TCE), and perchloroethylene (PCE), it was concluded that: (1) Freundlich’s model showed to be adequate to relate the contaminant contents in the gas phase with those in the solid and non-aqueous liquid phases; (2) the distribution of the contaminants in the different phases present in the soil could be estimated with differences lower than 10% for 83% of the cases; and (3) an increase of the soil water content led to a decrease of the amount of contaminant in the solid and non-aqueous liquid phases, increasing the amount in the other phases.

Contribution of hospital effluents to the load of pharmaceuticals in urban wastewaters: Identification of ecologically relevant pharmaceuticals

The impact of effluent wastewaters from four different hospitals: a university (1456 beds), a general (350 beds), a pediatric (110 beds) and a maternity hospital (96 beds), which are conveyed to the same wastewater treatment plant (WWTP), was evaluated in the receiving urban wastewaters. The occurrence of 78 pharmaceuticals belonging to several therapeutic classes was assessed in hospital effluents and WWTP wastewaters (influent and effluent) as well as the contribution of each hospital in WWTP influent in terms of pharmaceutical load. Results indicate that pharmaceuticals are widespread pollutants in both hospital and urban wastewaters. The contribution of hospitals to the input of pharmaceuticals in urban wastewaters widely varies, according to their dimension. The estimated total mass loadings were 306 g d− 1 for the university hospital, 155 g d− 1 for the general one, 14 g d− 1 for the pediatric hospital and 1.5 g d− 1 for the maternity hospital, showing that the biggest hospitals have a greater contribution to the total mass load of pharmaceuticals. Furthermore, analysis of individual contributions of each therapeutic group showed that NSAIDs, analgesics and antibiotics are among the groups with the highest inputs. Removal efficiency can go from over 90% for pharmaceuticals like acetaminophen and ibuprofen to not removal for β-blockers and salbutamol. Total mass load of pharmaceuticals into receiving surface waters was estimated between 5 and 14 g/d/1000 inhabitants. Finally, the environmental risk posed by pharmaceuticals detected in hospital and WWTP effluents was assessed by means of hazard quotients toward different trophic levels (algae, daphnids and fish). Several pharmaceuticals present in the different matrices were identified as potentially hazardous to aquatic organisms, showing that especial attention should be paid to antibiotics such as ciprofloxacin, ofloxacin, sulfamethoxazole, azithromycin and clarithromycin, since their hazard quotients in WWTP effluent revealed that they could pose an ecotoxicological risk to algae.

On the development of an automatic voice pleasantness classification and intensity estimation system

In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.

Distributed MPC for Thermal Comfort and Load Allocation with Energy Auction

This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using an integrated demand-side management approach that involves a power price auction and an appliance loads allocation scheme. The control objective for each subsystem (house or building) aims to minimize the energy cost while maintaining the indoor temperature inside comfort limits. In a distributed coordinated multi-agent ecosystem, each house or building control agent achieves its objectives while sharing, among them, the available energy through the introduction of particular coupling constraints in their underlying optimization problem. Coordination is maintained by a daily green energy auction bring in a demand-side management approach. Also the implemented distributed MPC algorithm is described and validated with simulation studies.

Radio link quality estimation in wireless sensor networks: a survey

Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and also affects the design of higher-layer protocols. Therefore, for about a decade, it has been attracting a vast array of research works. Reported works on link quality estimation are typically based on different assumptions, consider different scenarios, and provide radically different (and sometimes contradictory) results. This article provides a comprehensive survey on related literature, covering the characteristics of low-power links, the fundamental concepts of link quality estimation in WSNs, a taxonomy of existing link quality estimators, and their performance analysis. To the best of our knowledge, this is the first survey tackling in detail link quality estimation in WSNs. We believe our efforts will serve as a reference to orient researchers and system designers in this area.

Metaheuristic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Estimation and hypothesis testing in mixed linear models

Dissertação apresentada para obtenção do Grau de Doutor em Matemática, Estatística, pela Universidade Nova de Lisboa, faculdade de Ciências e Tecnologia

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

Analyzing objects in images for estimating the delamination influence on load carrying capacity of composite laminates

The use of fiber reinforced plastics has increased in the last decades due to their unique properties. Advantages of their use are related with low weight, high strength and stiffness. Drilling of composite plates can be carried out in conventional machinery with some adaptations. However, the presence of typical defects like delamination can affect mechanical properties of produced parts. In this paper delamination influence in bearing stress of drilled hybrid carbon+glass/epoxy quasi-isotropic plates is studied by using image processing and analysis techniques. Results from bearing test show that damage minimization is an important mean to improve mechanical properties of the joint area of the plate. The appropriateness of the image processing and analysis techniques used in the measurement of the damaged area is demonstrated.

Pose Estimation using a C-Arm Fluoroscope

Os métodos clínicos que são realizados com recurso a tecnologias de imagiologia têm registado um aumento de popularidade nas últimas duas décadas. Os procedimentos tradicionais usados em cirurgia têm sido substituídos por métodos minimamente invasivos de forma a conseguir diminuir os custos associados e aperfeiçoar factores relacionados com a produtividade. Procedimentos clínicos modernos como a broncoscopia e a cardiologia são caracterizados por se focarem na minimização de acções invasivas, com os arcos em ‘C’ a adoptarem um papel relevante nesta área. Apesar de o arco em ‘C’ ser uma tecnologia amplamente utilizada no auxílio da navegação em intervenções minimamente invasivas, este falha na qualidade da informação fornecida ao cirurgião. A informação obtida em duas dimensões não é suficiente para proporcionar uma compreensão total da localização tridimensional da região de interesse, revelando-se como uma tarefa essencial o estabelecimento de um método que permita a aquisição de informação tridimensional. O primeiro passo para alcançar este objectivo foi dado ao definir um método que permite a estimativa da posição e orientação de um objecto em relação ao arco em ‘C’. De forma a realizar os testes com o arco em ‘C’, a geometria deste teve que ser inicialmente definida e a calibração do sistema feita. O trabalho desenvolvido e apresentado nesta tese foca-se num método que provou ser suficientemente sustentável e eficiente para se estabelecer como um ponto de partida no caminho para alcançar o objectivo principal: o desenvolvimento de uma técnica que permita o aperfeiçoamento da qualidade da informação adquirida com o arco em ‘C’ durante uma intervenção clínica.

Estimation of vegetation carbon stock in Portugal using land use/ land cover data

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

Estimation of the Crustal Bulk Properties Beneath Mainland Portugal from P-Wave Teleseismic Receiver Functions

In this work, we present results from teleseismic P-wave receiver functions (PRFs) obtained in Portugal, Western Iberia. A dense seismic station deployment conducted between 2010 and 2012, in the scope of the WILAS project and covering the entire country, allowed the most spatially extensive probing on the bulk crustal seismic properties of Portugal up to date. The application of the H-κ stacking algorithm to the PRFs enabled us to estimate the crustal thickness (H) and the average crustal ratio of the P- and S-waves velocities V p/V s (κ) for the region. Observations of Moho conversions indicate that this interface is relatively smooth with the crustal thickness ranging between 24 and 34 km, with an average of 30 km. The highest V p/V s values are found on the Mesozoic-Cenozoic crust beneath the western and southern coastal domain of Portugal, whereas the lowest values correspond to Palaeozoic crust underlying the remaining part of the subject area. An average V p/V s is found to be 1.72, ranging 1.63-1.86 across the study area, indicating a predominantly felsic composition. Overall, we systematically observe a decrease of V p/V s with increasing crustal thickness. Taken as a whole, our results indicate a clear distinction between the geological zones of the Variscan Iberian Massif in Portugal, the overall shape of the anomalies conditioned by the shape of the Ibero-Armorican Arc, and associated Late Paleozoic suture zones, and the Meso-Cenozoic basin associated with Atlantic rifting stages. Thickened crust (30-34 km) across the studied region may be inherited from continental collision during the Paleozoic Variscan orogeny. An anomalous crustal thinning to around 28 km is observed beneath the central part of the Central Iberian Zone and the eastern part of South Portuguese Zone.

Velocity estimation of moving ships using C-band SLC SAR data

A new algorithm for the velocity vector estimation of moving ships using Single Look Complex (SLC) SAR data in strip map acquisition mode is proposed. The algorithm exploits both amplitude and phase information of the Doppler decompressed data spectrum, with the aim to estimate both the azimuth antenna pattern and the backscattering coefficient as function of the look angle. The antenna pattern estimation provides information about the target velocity; the backscattering coefficient can be used for vessel classification. The range velocity is retrieved in the slow time frequency domain by estimating the antenna pattern effects induced by the target motion, while the azimuth velocity is calculated by the estimated range velocity and the ship orientation. Finally, the algorithm is tested on simulated SAR SLC data.