Multi-elemental analysis of ready-to-eat “baby leaf” vegetables using microwave digestion and high-resolution continuum source atomic absorption spectrometry

The mineral content (phosphorous (P), potassium (K), sodium (Na), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), zinc (Zn) and copper (Cu)) of eight ready-to-eat baby leaf vegetables was determined. The samples were subjected to microwave-assisted digestion and the minerals were quantified by High-Resolution Continuum Source Atomic Absorption Spectrometry (HR-CS-AAS) with flame and electrothermal atomisation. The methods were optimised and validated producing low LOQs, good repeatability and linearity, and recoveries, ranging from 91% to 110% for the minerals analysed. Phosphorous was determined by a standard colorimetric method. The accuracy of the method was checked by analysing a certified reference material; results were in agreement with the quantified value. The samples had a high content of potassium and calcium, but the principal mineral was iron. The mineral content was stable during storage and baby leaf vegetables could represent a good source of minerals in a balanced diet. A linear discriminant analysis was performed to compare the mineral profile obtained and showed, as expected, that the mineral content was similar between samples from the same family. The Linear Discriminant Analysis was able to discriminate different samples based on their mineral profile.

Multi-dimensional scaling applied to histogram-based DNA analysis

This paper aims to study the relationships between chromosomal DNA sequences of twenty species. We propose a methodology combining DNA-based word frequency histograms, correlation methods, and an MDS technique to visualize structural information underlying chromosomes (CRs) and species. Four statistical measures are tested (Minkowski, Cosine, Pearson product-moment, and Kendall τ rank correlations) to analyze the information content of 421 nuclear CRs from twenty species. The proposed methodology is built on mathematical tools and allows the analysis and visualization of very large amounts of stream data, like DNA sequences, with almost no assumptions other than the predefined DNA “word length.” This methodology is able to produce comprehensible three-dimensional visualizations of CR clustering and related spatial and structural patterns. The results of the four test correlation scenarios show that the high-level information clusterings produced by the MDS tool are qualitatively similar, with small variations due to each correlation method characteristics, and that the clusterings are a consequence of the input data and not method’s artifacts.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

A framework for memory contention analysis in multi-core platforms

The last decade has witnessed a major shift towards the deployment of embedded applications on multi-core platforms. However, real-time applications have not been able to fully benefit from this transition, as the computational gains offered by multi-cores are often offset by performance degradation due to shared resources, such as main memory. To efficiently use multi-core platforms for real-time systems, it is hence essential to tightly bound the interference when accessing shared resources. Although there has been much recent work in this area, a remaining key problem is to address the diversity of memory arbiters in the analysis to make it applicable to a wide range of systems. This work handles diverse arbiters by proposing a general framework to compute the maximum interference caused by the shared memory bus and its impact on the execution time of the tasks running on the cores, considering different bus arbiters. Our novel approach clearly demarcates the arbiter-dependent and independent stages in the analysis of these upper bounds. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to the contention for the bus. We show that the framework addresses the diversity problem by applying it to a memory bus shared by a fixed-priority arbiter, a time-division multiplexing (TDM) arbiter, and an unspecified work-conserving arbiter using applications from the MediaBench test suite. We also experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.

Energy analysis of Multi-legged Locomotion Systems

4th International Conference on Climbing and Walking Robots - From Biology to Industrial Applications

DITRANS - a multi-agent system for integrated diagnosis of power transformers

This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Factores de rentabilização do processo de serragem de granitos com engenhos multi-lâminas

Este trabalho visa apresentar um enquadramento da realidade económica e industrial do sector transformador de granitos ornamentais em Portugal e fazer uma análise do processo de serragem, com engenhos multi-lâminas e granalha de aço, na medida em que este é o método de seccionamento de blocos de granito mais utilizado pelas grandes indústrias do sector. Tendo em conta a importância económica desta operação produtiva na indústria em causa, foi definido como fito deste projecto a análise estatística dos custos de produção; a definição de fórmulas de cálculo que permitam prever o custo médio de serragem; e o estudo de soluções economicamente viáveis e ambientalmente sustentáveis para o problema das lamas resultantes do expurgo dos engenhos. Para a persecução deste projecto foi realizada uma recolha de dados implementando rotinas de controlo e registo dos mesmos, em quadros de produção normalizados e de fácil preenchimento, pelos operadores destes equipamentos. Esta recolha de dados permitiu isolar, quantificar e formular os factores de rentabilização do processo de serragem selecionando, dentro da amostra de estudo obtida, um conjunto de serragens com características similares e com valores próximos dos valores da média estatística. Apartir dos dados destas serragens foram geradas curvas de tendência polinomial com as quais se analisaram as variações provocadas no custo médio de serragem, pelas variações do factor em estudo. A formulação dos factores de rentabilização e os dados estatísticos obtidos permitiram depois o desenvolvimento de fórmulas de cálculo do custo médio de serragem que establecem o custo de produção diferenciado em função das espessuras com, ou sem, a incorporação dos factores de rentabilização. Como consequência do projecto realizado obteve-se um conjunto de conclusões util, para o sector industrial em causa, que evidencia a importancia da Ocupação dos engenhos e rentabilização de um espaço confinado, da Resistência oferecida à serragem pelos granitos, e da Diferença de altura entre os blocos de uma mesma carga, nos custos de transformação.

Biosensor based on multi-walled carbon nanotubes paste electrode modified with laccase for pirimicarb pesticide quantification

This study focused on the development of a sensitive enzymatic biosensor for the determination of pirimicarb pesticide based on the immobilization of laccase on composite carbon paste electrodes. Multi- walled carbon nanotubes(MWCNTs)paste electrode modified by dispersion of laccase(3%,w/w) within the optimum composite matrix(60:40%,w/w,MWCNTs and paraffin binder)showed the best performance, with excellent electron transfer kinetic and catalytic effects related to the redox process of the substrate4- aminophenol. No metal or anti-interference membrane was added. Based on the inhibition of laccase activity, pirimicarb can be determined in the range 9.90 ×10- 7 to 1.15 ×10- 5 molL 1 using 4- aminophenol as substrate at the optimum pH of 5.0, with acceptable repeatability and reproducibility (relative standard deviations lower than 5%).The limit of detection obtained was 1.8 × 10-7 molL 1 (0.04 mgkg 1 on a fresh weight vegetable basis).The high activity and catalytic properties of the laccase- based biosensor are retained during ca. one month. The optimized electroanalytical protocol coupled to the QuEChERS methodology were applied to tomato and lettuce samples spiked at three levels; recoveries ranging from 91.0±0.1% to 101.0 ± 0.3% were attained. No significant effects in the pirimicarb electro- analysis were observed by the presence of pro-vitamin A, vitamins B1 and C,and glucose in the vegetable extracts. The proposed biosensor- based pesticide residue methodology fulfills all requisites to be used in implementation of food safety programs.

Strategic bidding in electricity markets: an agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Supporting real-time distributed computer-controlled systems with multi-hop P-NET networks

Fieldbus communication networks aim to interconnect sensors, actuators and controllers within process control applications. Therefore, they constitute the foundation upon which real-time distributed computer-controlled systems can be implemented. P-NET is a fieldbus communication standard, which uses a virtual token-passing medium-access-control mechanism. In this paper pre-run-time schedulability conditions for supporting real-time traffic with P-NET networks are established. Essentially, formulae to evaluate the upper bound of the end-to-end communication delay in P-NET messages are provided. Using this upper bound, a feasibility test is then provided to check the timing requirements for accessing remote process variables. This paper also shows how P-NET network segmentation can significantly reduce the end-to-end communication delays for messages with stringent timing requirements.

Communication response time in P-NET networks: worst-case analysis considering the actual token utilisation

Fieldbus networks aim at the interconnection of field devices such as sensors, actuators and small controllers. Therefore, they are an effective technology upon which Distributed Computer Controlled Systems (DCCS) can be built. DCCS impose strict timeliness requirements to the communication network. In essence, by timeliness requirements we mean that traffic must be sent and received within a bounded interval, otherwise a timing fault is said to occur. P-NET is a multi-master fieldbus standard based on a virtual token passing scheme. In P-NET each master is allowed to transmit only one message per token visit, which means that in the worst-case the communication response time could be derived considering that the token is fully utilised by all stations. However, such analysis can be proved to be quite pessimistic. In this paper we propose a more sophisticated P-NET timing analysis model, which considers the actual token utilisation by different masters. The major contribution of this model is to provide a less pessimistic, and thus more accurate, analysis for the evaluation of the worst-case communication response time in P-NET fieldbus networks.

Preliminary discussion on globally prioritized medium access for multi-channel wireless systems

We discuss the development of a simple globally prioritized multi-channel medium access control (MAC) protocol for wireless networks. This protocol provides “hard” pre-run-time real-time guarantees to sporadic message streams, exploits a very large fraction of the capacity of all channels for “hard” real-time traffic and also makes it possible to fully utilize the channels with non real-time traffic when hard real-time messages do not request to be transmitted. The potential of such protocols for real-time applications is discussed and a schedulability analysis is also presented.

CardioML: integrating personal cardiac information for ubiquous diagnosis and analysis

The latest medical diagnosis devices enable the performance of e-diagnosis making the access to these services easier, faster and available in remote areas. However this imposes new communications and data interchange challenges. In this paper a new XML based format for storing cardiac signals and related information is presented. The proposed structure encompasses data acquisition devices, patient information, data description, pathological diagnosis and waveform annotation. When compared with similar purpose formats several advantages arise. Besides the full integrated data model it may also be noted the available geographical references for e-diagnosis, the multi stream data description, the ability to handle several simultaneous devices, the possibility of independent waveform annotation and a HL7 compliant structure for common contents. These features represent an enhanced integration with existent systems and an improved flexibility for cardiac data representation.

Gestão de multi-projeto no processo de desenvolvimento de produto

No âmbito da unidade curricular Dissertação/Projeto/Estágio do 2º ano do Mestrado em Engenharia mecânica – Ramo Gestão Industrial do Instituto Superior de Engenharia do Porto, o presente trabalho de dissertação foi enquadrado num projeto de desenvolvimento de ferramentas de apoio à gestão de projetos. O projeto foi desenvolvido no Instituto de Engenharia Mecânica e Gestão Industrial (INEGI) na unidade de Desenvolvimento de Produto e Sistemas (DPS). A realização deste projeto teve como objetivo o desenvolvimento e adequação de ferramentas de apoio à gestão de multi-projeto no processo de desenvolvimento de produto na organização em estudo – o INEGI – DPS. A gestão de projetos tem hoje uma grande importância nos resultados das empresas essencialmente em virtude da necessidade de estas competirem num mundo em grande mudança com concorrentes ferozes, em que a capacidade de responder às mudanças a tempo e de uma forma integrada se torna cada vez mais importante. A atividade levada a cabo pela DPS impõe a necessidade de uma gestão de projetos mais eficaz e eficiente suportada numa gestão de informação centralizada. O presente projeto de investigação teve, numa primeira fase, uma adaptação à organização em estudo. De seguida, foi conduzida uma revisão da literatura com o objetivo de se obter a fundamentação teórica necessária ao desenvolvimento de ferramentas com base nas metodologias lean. Prosseguiu com o levantamento da situação inicial da organização e com a identificação dos problemas existentes na gestão de projetos. Incluiu também uma revisão e análise das ferramentas existentes na unidade em estudo. Este conhecimento permitiu delinear uma visão para guiar o desenvolvimento das ferramentas. Após a definição da visão foi, então, realizado o desenvolvimento das ferramentas de auxílio à gestão multi-projeto na organização. A concretização deste trabalho resultou no desenvolvimento de três ferramentas de auxílio à gestão multi-projeto na unidade. Estas ferramentas tornam o processo de gestão de projetos mais simples e fácil de assimilar, requerendo apenas alguns inputs por parte dos colaboradores. Estas ferramentas estão apoiadas nos pilares do lean, e deste modo estão vocacionadas para reduzir o desperdício, promover a melhoria contínua, aumentar o desempenho global dos vários atores nos projetos de modo a entregar mais valor e qualidade superior com menores custos. Acima de tudo, valorizar o trabalho dos colaboradores, tornando-os mais eficientes, eficazes, motivados e comprometidos com a organização.