A Hybrid Simulated Annealing approach to handle Energy Resource Management considering an intensive use of Electric Vehicles

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.

An Approach To Publish a Data Warehouse Content as Linked Data

Mestrado em Engenharia Informática - Área de Especialização em Tecnologias do Conhecimento e Decisão

EduMCA: an approach to Educational Mobile Content Adaptation

As the variety of mobile devices connected to the Internet growts there is a correponding increase in the need to deliver content tailored to their heterogeneous characteristics. At the same time, we watch to the increase of e-learning in universities through the adoption of electronic platforms and standards. Not surprisingly, the concept of mLearning (Mobile Learning) appeared in recent years decreasing the limitation of learning location with the mobility of general portable devices. However, this large number and variety of Web-enabled devices poses several challenges for Web content creators who want to automatic get the delivery context and adapt the content to the client mobile devices. In this paper we analyze several approaches to defining delivery context and present an architecture for deliver uniform mLearning content to mobile devices denominated eduMCA - Educational Mobile Content Adaptation. With the eduMCA system the Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.

Utilização de redes neuronais artificiais na gestão de processos de digestão anaeróbia

Numa Estação de Tratamento de Águas Residuais (ETAR), a otimização do processo de Digestão Anaeróbia (DA) é fundamental para o aumento da produção de biogás, que por sua vez é convertido em energia, essencial para a rentabilidade de exploração de ETAR. No entanto, a complexidade do processo de Digestão Anaeróbia das lamas constitui um obstáculo à sua otimização. Com este trabalho pretende-se efetuar a análise e tratamento de dados de Digestão Anaeróbia, com recurso a Redes Neuronais Artificiais (RNA), contribuindo, desta forma, para a compreensão do processo e do impacto de algumas variáveis na produção de biogás. As Redes Neuronais Artificiais são modelos matemáticos computacionais inspirados no funcionamento do cérebro humano, com capacidade para entender relações complexas num determinado conjunto de dados, motivo por que se optou pela sua utilização na procura de soluções que permitem predizer o comportamento de uma DA. Para o desenvolvimento das RNA utilizou-se o programa NeuralToolsTM da PalisadeTM. Como caso de estudo, a metodologia foi aplicada ao Digestor A da ETAR Sul da SIMRIA, empresa onde teve lugar o estágio curricular que originou o presente trabalho. Nesse contexto, utilizaram-se dados com informação referente aos últimos dois anos de funcionamento do digestor, disponíveis na empresa. Apesar de se terem verificado certas limitações, na predição em alguns casos particulares, de um modo geral, considera-se que os resultados obtidos permitiram concluir que as redes neuronais modeladas apresentam boa capacidade de generalização na imitação do processo anaeróbio. Conclui-se, portanto, que o estudo realizado pode constituir um contributo com interesse para a otimização da produção do biogás na DA de ETAR Sul da SIMRIA e que a utilização de RNA poderá ser uma ferramenta a explorar, quer nessa área, quer noutras áreas de gestão de sistemas de saneamento básico.

A novel antibody-like material for breast cancer antigen CA15-3, used to track breast cancer by potentiometric transduction

This work presents the development of a low cost sensor device for the diagnosis of breast cancer in point-of-care, made with new synthetic biomimetic materials inside plasticized poly(vinyl chloride), PVC, membranes, for subsequent potentiometric detection. This concept was applied to target a conventional biomarker in breast cancer: Breast Cancer Antigen (CA15-3). The new biomimetic material was obtained by molecularly-imprinted technology. In this, a plastic antibody was obtained by polymerizing around the biomarker that acted as an obstacle to the growth of the polymeric matrix. The imprinted polymer was specifically synthetized by electropolymerization on an FTO conductive glass, by using cyclic voltammetry, including 40 cycles within -0.2 and 1.0 V. The reaction used for the polymerization included monomer (pyrrol, 5.0×10-3 mol/L) and protein (CA15-3, 100U/mL), all prepared in phosphate buffer saline (PBS), with a pH of 7.2 and 1% of ethylene glycol. The biomarker was removed from the imprinted sites by proteolytic action of proteinase K. The biomimetic material was employed in the construction of potentiometric sensors and tested with regard to its affinity and selectivity for binding CA15-3, by checking the analytical performance of the obtained electrodes. For this purpose, the biomimetic material was dispersed in plasticized PVC membranes, including or not a lipophilic ionic additive, and applied on a solid conductive support of graphite. The analytical behaviour was evaluated in buffer and in synthetic serum, with regard to linear range, limit of detection, repeatability, and reproducibility. This antibody-like material was tested in synthetic serum, and good results were obtained. The best devices were able to detect 5 times less CA15-3 than that required in clinical use. Selectivity assays were also performed, showing that the various serum components did not interfere with this biomarker. Overall, the potentiometric-based methods showed several advantages compared to other methods reported in the literature. The analytical process was simple, providing fast responses for a reduced amount of analyte, with low cost and feasible miniaturization. It also allowed the detection of a wide range of concentrations, diminishing the required efforts in previous sample pre-treating stages.