Technology for creativity and innovation: tools, techniques and applications

It is widely accepted that organizations and individuals must be innovative and continually create new knowledge and ideas to deal with rapid change. Innovation plays an important role in not only the development of new business, process and products, but also in competitiveness and success of any organization. Technology for Creativity and Innovation: Tools, Techniques and Applications provides empirical research findings and best practices on creativity and innovation in business, organizational, and social environments. It is written for educators, academics and professionals who want to improve their understanding of creativity and innovation as well as the role technology has in shaping this discipline.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

Molecular imprinted nanoelectrodes for ultra sensitive detection of ovarian cancer marker

The relentless discovery of cancer biomarkers demands improved methods for their detection. In this work, we developed protein imprinted polymer on three-dimensional gold nanoelectrode ensemble (GNEE) to detect epithelial ovarian cancer antigen-125 (CA 125), a protein biomarker associated with ovarian cancer. CA 125 is the standard tumor marker used to follow women during or after treatment for epithelial ovarian cancer. The template protein CA 125 was initially incorporated into the thin-film coating and, upon extraction of protein from the accessible surfaces on the thin film, imprints for CA 125 were formed. The fabrication and analysis of the CA 125 imprinted GNEE was done by using cyclic voltammetry (CV), differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) techniques. The surfaces of the very thin, protein imprinted sites on GNEE are utilized for immunospecific capture of CA 125 molecules, and the mass of bound on the electrode surface can be detected as a reduction in the faradic current from the redox marker. Under optimal conditions, the developed sensor showed good increments at the studied concentration range of 0.5–400 U mL−1. The lowest detection limit was found to be 0.5 U mL−1. Spiked human blood serum and unknown real serum samples were analyzed. The presence of non-specific proteins in the serum did not significantly affect the sensitivity of our assay. Molecular imprinting using synthetic polymers and nanomaterials provides an alternative approach to the trace detection of biomarker proteins.

Autoxidação de ácidos gordos na presença de antioxidantes naturais e sintéticos

Nas últimas décadas, devido ao desenvolvimento económico, e a uma necessidade constante de gerir os recursos energéticos, existe uma necessidade de procurar novas fontes de energia, em particular fontes de energia renováveis. O biodiesel surge assim como uma energia alternativa ao combustível fóssil. Este biocombustível tem ganho uma importância significativa na sociedade moderna. Quimicamente o biodiesel é constituído por ésteres metílicos de ácidos gordos de cadeia longa, derivados de óleos vegetais ou gorduras animais. O principal problema que este enfrenta é a sua susceptibilidade à oxidação, devido ao seu conteúdo de ácidos gordos insaturados, logo existe uma procura constante de soluções que possam solucionar este problema. É necessária a identificação de técnicas e métodos para retardar a seu envelhecimento ao longo do tempo. O objectivo deste trabalho consiste no estudo da estabilidade do biodiesel ao longo do tempo, quando armazenado a diferentes condições de temperatura, superiores às normalmente suportadas pelo biodiesel durante o armazenamento, de modo a acelerar o processo de degradação. As amostras de biodiesel foram sujeitas a duas temperaturas. Uma amostra de biodiesel não estabilizado foi colocada a uma temperatura entre 40 e 50ºC ao longo de 203 dias, e uma outra amostra foi colocada a uma temperatura entre 95º e 105ºC ao longo de 146 dias. Realizaram-se ensaios semanais de modo registar a evolução do envelhecimento do biodiesel. As análises foram efectuadas por espectrofotometria de ultravioleta e visível (UV-VIS) e por espectroscopia de absorção na região do infravermelho (FTIR). No UV-VIS foi possível observar que o aumento de temperatura foi responsável pela aceleração da oxidação do biodiesel que resulta num aumento generalizado da absorvância do biodiesel. Através das análises efectuadas no FTIR verificou-se a formação e aumento da banda dos hidroperóxidos (grupo ROOH) localizada entre 3000 e 3600 cm-1 nos espectros, e igualmente um alargamento na banda dos carbonilos (grupo C=O) entre 1500 e 1900 cm-1. Numa fase posterior testaram-se antioxidantes para retardar o envelhecimento do biodiesel. Os ensaios foram efectuados a uma temperatura entre 95º e 105ºC. Os antioxidantes utilizados foram o galhato de propilo (PG), o galhato de etilo (EG) e o ácido gálhico (AG). Recorreu-se a técnicas como o UV-VIS e o FTIR para o registo dos espectros do biodiesel ao longo do tempo. Através destas técnicas foi possível verificar a influência de antioxidantes na estabilidade oxidativa do biodiesel. O PG foi o antioxidante que melhor desempenho mostrou no retardamento da oxidação do biodiesel e a técnica que melhor permitiu analisar a acção dos antioxidantes foi o UVVIS. Os resultados obtidos por FTIR não se mostraram tão conclusivos. Para caracterizar o envelhecimento do biodiesel não estabilizado e estabilizado utilizou-se também a cromatografia gasosa (CG) para quantificar a percentagem de ésteres metílicos presentes nas diferentes amostras no inicio e no fim do processo de oxidação. O biodiesel envelheceu mais rapidamente para temperaturas mais elevadas e comprovou-se que o antioxidante que melhor estabiliza o biodiesel é o PG.

Agrupamento de dados visual interactivo

Com a crescente geração, armazenamento e disseminação da informação nos últimos anos, o anterior problema de falta de informação transformou-se num problema de extracção do conhecimento útil a partir da informação disponível. As representações visuais da informação abstracta têm sido utilizadas para auxiliar a interpretação os dados e para revelar padrões de outra forma escondidos. A visualização de informação procura aumentar a cognição humana aproveitando as capacidades visuais humanas, de forma a tornar perceptível a informação abstracta, fornecendo os meios necessários para que um humano possa absorver quantidades crescentes de informação, com as suas capacidades de percepção. O objectivo das técnicas de agrupamento de dados consiste na divisão de um conjunto de dados em vários grupos, em que dados semelhantes são colocados no mesmo grupo e dados dissemelhantes em grupos diferentes. Mais especificamente, o agrupamento de dados com restrições tem o intuito de incorporar conhecimento a priori no processo de agrupamento de dados, com o objectivo de aumentar a qualidade do agrupamento de dados e, simultaneamente, encontrar soluções apropriadas a tarefas e interesses específicos. Nesta dissertação é estudado a abordagem de Agrupamento de Dados Visual Interactivo que permite ao utilizador, através da interacção com uma representação visual da informação, incorporar o seu conhecimento prévio acerca do domínio de dados, de forma a influenciar o agrupamento resultante para satisfazer os seus objectivos. Esta abordagem combina e estende técnicas de visualização interactiva de informação, desenho de grafos de forças direccionadas e agrupamento de dados com restrições. Com o propósito de avaliar o desempenho de diferentes estratégias de interacção com o utilizador, são efectuados estudos comparativos utilizando conjuntos de dados sintéticos e reais.

Síntese de derivados de ácidos fenólicos e estudo da sua actividade antioxidante

A peroxidação lipídica, além de causar sérios danos no corpo humano, é a principal causa da deterioração dos alimentos afectando a sua cor, aroma e valor nutricional, o que conduz a uma diminuição do seu ciclo de vida. O fenómeno de oxidação pode ser retardado com recurso a antioxidantes, de origem natural ou sintética, que inibam a formação de espécies reactivas, ou que reajam com estas, formando posteriormente radicais com menor grau de reactividade. Nesta dissertação procedeu-se à síntese e elucidação estrutural de novos antioxidantes, derivados dos ácidos 3,4-diidroxibenzóico (PCA) e 3,4-diidroxifenilacético (DOPAC), e à avaliação da sua actividade anti-radicalar e antioxidante. Os novos antioxidantes sintetizados foram caracterizados usando RMN de 1H e de 13C, FTIR e EM-IE. A avaliação da actividade antioxidante foi realizada com base no método do radical 2,2- difenil-1-picrilhidrazilo (DPPH·) e por técnicas electroquímicas (voltametria de impulso diferencial e voltametria cíclica). Os resultados obtidos permitiram concluir que a eficácia anti-radicalar (AE) é determinada por aspectos da estrutura molecular dos compostos, nomeadamente pela presença de grupos hidroxilo no anel aromático e também de grupos extensores relativamente à posição do grupo carboxílico. Os resultados permitiram verificar que o DOPAC apresenta a mais elevada eficiência anti-radicalar dos compostos em estudo, incluindo o trolox e o ácido gálhico (compostos de referência). Com base nos resultados obtidos concluiu-se que, um menor potencial de oxidação conduz a uma melhor actividade anti-radicalar dos compostos. De facto, verificou-se para o PCA e respectivos ésteres o maior potencial de oxidação e também a menor eficiência anti-radicalar. Em contrapartida, os antioxidantes com maior eficiência anti-radicalar, DOPAC, trolox e ácido gálhico, apresentaram menor potencial de oxidação.

Magnetic resonance imaging of the vocal tract: techniques and applications

Magnetic resonance (MR) imaging has been used to analyse and evaluate the vocal tract shape through different techniques and with promising results in several fields. Our purpose is to demonstrate the relevance of MR and image processing for the vocal tract study. The extraction of contours of the air cavities allowed the set - up of a number of 3D reconstruction image stacks by means of the combination of orthogonally oriented sets of slices for e ach articulatory gesture, as a new approach to solve the expected spatial under sampling of the imaging process. In result these models give improved information for the visualization of morphologic and anatomical aspects and are useful for partial measure ments of the vocal tract shape in different situations. Potential use can be found in Medical and therapeutic applications as well as in acoustic articulatory speech modelling.