Soft-computing techniques applied to artificial tissue temperature estimation

Tese dout., Engenharia electrónica e computação - Processamento de sinal, Universidade do Algarve, 2008

A produção de bioetanol e a mitigação dos gases de efeito de estufa: o contributo das culturas energéticas no regadio de Alqueva

Dissertação mest., Gestão Sustentável dos Espaços Rurais, Universidade do Algarve, 2008

Bottom-up regulation of phytoplankton in the Guadiana estuary

Tese dout., Ciências do Mar (Ecologia Marinha), Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2010

Model comparison for temperature estimation inside buildings

This paper presents a comparison between a physical model and an artificial neural network model (NN) for temperature estimation inside a building room. Despite the obvious advantages of the physical model for structure optimisation purposes, this paper will test the performance of neural models for inside temperature estimation. The great advantage of the NN model is a big reduction of human effort time, because it is not needed to develop the structural geometry and structural thermal capacities and to simulate, which consumes a great human effort and great computation time. The NN model deals with this problem as a “black box” problem. We describe the use of the Radial Basis Function (RBF), the training method and a multi-objective genetic algorithm for optimisation/selection of the RBF neural network inputs and number of neurons.

A greenhouse climate multivariable predictive controller

A multivariable predictive controller was implemented to regulate the air temperature, humidity and CO2 concentration for a greenhouse located in the north of Portugal. The controller outputs are computed in order to optimise the future behaviour of the greenhouse environment, concerning the set-point accuracy and the minimization of energy inputs.

Identification of greenhouse climate dynamic models

In this paper climate discrete-time dynamic models for the inside air temperature of two different greenhouses are identified, using data acquired during two different periods of the year. These models employ data from air temperature and relative humidity (both outside and inside the greenhouse), solar radiation, wind speed, and control inputs (ventialtion, etc.).

Prediction of the solar radiation using RBF neural networks and ground-to-sky images

In this study, Artificial Neural Networks are applied to multistep long term solar radiation prediction. The networks are trained as one-step-ahead predictors and iterated over time to obtain multi-step longer term predictions. Auto-regressive and Auto-regressive with exogenous inputs solar radiationmodels are compared, considering cloudiness indices as inputs in the latter case. These indices are obtained through pixel classification of ground-to-sky images. The input-output structure of the neural network models is selected using evolutionary computation methods.

Modelos e estratégias de controlo ambientais para estufas agrícolas

For a greenhouse with a double polyethylene cover, it will be presented a dynamic climate transfer function and an adaptive controller for the air temperature. The model employ data acquired from the outside weather and from the heating and cooling inputs.

O uso do data envelopment analysis para avaliação e melhoria de desempenho no setor bancário: estudo de caso

O presente estudo aborda o uso do Data Envelopment Analysis (DEA) para avaliar e melhorar o desempenho no setor bancário. Consiste num estudo de caso aplicado a um dos maiores bancos portugueses. O seu objetivo, é avaliar a eficiência relativa das 333 agências bancárias que formam um dos dois departamentos comerciais do banco. Pretende-se identificar boas práticas e verificar a sua aplicabilidade nas unidades menos eficientes por forma a contribuir para a melhoria do desempenho global da instituição. Ao mesmo tempo, comparam-se os resultados de eficiência obtidos com o desempenho das unidades de negócio no cumprimento dos seus objetivos comerciais. Procura-se, assim, analisar a eventual existência de correlação entre eficiência e eficácia, ou seja, se as agências bancárias mais eficientes são também as mais eficazes. Para o efeito, é construído um modelo DEA que, considera em simultâneo, vários inputs e outputs. No modelo, as variáveis de input agregam os custos das unidades de negócio e as variáveis de output, os seus principais proveitos e alguns dos aspetos estratégicos que o banco pretende maximizar. Os resultados obtidos, identificam não só as agências bancárias menos eficientes, como assinalam aquelas que sendo semelhantes e eficientes, lhes podem servir de referência para a melhoria do seu desempenho. Tendo em conta, o caráter formativo que se pretende para o estudo, e de modo a facilitar a aceitação pelos decisores, procura-se verificar a exequibilidade das propostas apresentadas. O documento conclui pela existência, nas unidades de negócio analisadas, de uma correlação positiva fraca entre eficiência e eficácia, ainda assim estatisticamente significante. Por último, assinala a importância da metodologia DEA, enquanto medida de complementaridade de outras técnicas de controlo de gestão, em particular nas organizações que adotam a gestão por objetivos.

Modelfest and contrast-interrelation-function data predicted by a retinal model

The automatic implementation of decoders for a visual perception is achieved as follows. The action described by a production rule is realized by means of the decoder in which a pattern of connections coreesponds to that of stimuli. According to "S.Karasawa,(Proc. of CCCT, Vol.5, pp.194-1999, Austin, Texas, August, 2004)", each program mable controllable connection among inputs is realized by a floating gate avalanche injection MOS FET, where inverted signals are used at writing, and the detection of matching between inputs and connections is carried out by using the signal source in which low level signal is provided via comparatively smaller resistance than high level.

Habitat use and diel vertical migration of bigeye thresher shark: overlap with pelagic longline fishing gear

Pelagic longliners targeting swordfish and tunas in oceanic waters regularly capture sharks as bycatch, including currently protected species as the bigeye thresher, Alopias superciliosus. Fifteen bigeye threshers were tagged with pop-up satellite archival tags (PSATs) in 2012-2014 in the tropical northeast Atlantic, with successful transmissions received from 12 tags for a total of 907 tracking days. Marked diel vertical movements were recorded on all specimens, with most of the daytime spent in deeper colder water (mean depth = 353 m, SD = 73; mean temperature = 10.7 °C, SD = 1.8) and nighttime spent in warmer water closer to the surface (mean depth = 72 m, SD = 54; mean temperature = 21.9 °C, SD = 3.7). The operating depth of the pelagic longline gear was measured with Minilog Temperature and Depth Recorders (TDRs), and the overlap with habitat utilization was calculated. Overlap is taking place mainly during the night and is higher for juveniles. The results presented herein can be used as inputs for Ecological Risk Assessments for bigeye threshers captured in oceanic tuna fisheries, and serve as a basis for efficient management and conservation of this vulnerable shark species.

Catchment influences on the hydrological flows to lake terra alta (Linhares, ES, Brazil) and ecohydrology perspectives

Dissertação de mestrado, Ecohidrologia, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015