Método multicritério como apoio a um processo de negociação numa empresa de serviços médicos

O processo de negociação tem ganho relevância como uma das formas de gestão de conflitos. Verifica-se que nas organizações a negociação é um processo omnipresente, que tem sido alvo de muito estudo e investigação, e as capacidades de negociação são consideradas determinantes para o sucesso. Em consequência dessas tendências, surgem propostas de modelos de negociação bastantes flexíveis e que visam colaboração entre as partes interessadas, modelos que se adequam aos contextos organizacionais em que predominam relações estáveis e de longo prazo. Estas propostas procuram a solução óptima para as partes interessadas. No entanto, faltam frequentemente os mecanismos e procedimentos que garantam um processo estruturado para elaborar e analisar os diversos cenários na negociação, considerando um conjunto de aspectos relevantes para ambas as partes. No presente trabalho de dissertação formula-se uma proposta baseada no modelo de negociação Win Win Quantitativa, em que foi utilizada uma abordagem do método multicritério Analitic Hierarchy Process (AHP) para seleccionar a melhor opção de serviço para uma determinada empresa. Para o caso de estudo, num contexto real, foi necessário desenvolver uma aplicação Excel que permitisse analisar, de uma forma clara, as diversas alternativas perante os critérios mencionados. A aplicação do método AHP permite aos clientes tomar uma decisão potencialmente mais acertada. A aplicação informática procura optimizar os custos inerentes à prestação de serviços, oferecendo aos clientes um custo reduzido e assim tornando a empresa mais competitiva e atractiva para os potenciais clientes.

Fuzzy Monte Carlo model for transmission power systems reliability based decision making

This thesis presents the Fuzzy Monte Carlo Model for Transmission Power Systems Reliability based studies (FMC-TRel) methodology, which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states. This is followed by a remedial action algorithm, based on Optimal Power Flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. For the system states that cause load curtailment, an optimization approach is applied to reduce the probability of occurrence of these states while minimizing the costs to achieve that reduction. This methodology is of most importance for supporting the transmission system operator decision making, namely in the identification of critical components and in the planning of future investments in the transmission power system. A case study based on Reliability Test System (RTS) 1996 IEEE 24 Bus is presented to illustrate with detail the application of the proposed methodology.

Static and hydrodynamic monitoring of citalopram based on its electro-oxidation behavior at a glassy-carbon surface

The electrooxidative behavior of citalopram (CTL) in aqueous media was studied by cyclic voltammetry (CV) and square-wave voltammetry (SWV) at a glassy-carbon electrode. The electrochemical behaviour of CTL involves two electrons and two protons in the irreversible and diffusion controlled oxidation of the tertiary amine group. The maximum analytical signal was obtained in a phosphate buffer (pH ¼ 8.2). For analytical purposes, an SWV method and a flow-injection analysis (FIA) system with amperometric detection were developed. The optimised SWV method showed a linear range between 1.10 10 5–1.20 10 4 molL 1, with a limit of detection (LOD) of 9.5 10 6 molL 1. Using the FIA method, a linear range between 2.00 10 6–9.00 10 5 molL 1 and an LODof 1.9 10 6 molL 1 were obtained. The validation of both methods revealed good performance characteristics confirming applicability for the quantification of CTL in several pharmaceutical products.

Square-wave voltametric method for determination of molinate concentration in a biological process using a hanging mercury drop electrode

A square-wave voltammetric (SWV) method using a hanging mercury drop electrode (HMDE) has been developed for determination of the herbicide molinate in a biodegradation process. The method is based on controlled adsorptive accumulation of molinate for 10 s at a potential of -0.8 V versus AgCl/Ag. An anodic peak, due to oxidation of the adsorbed pesticide, was observed in the cyclic voltammogram at ca. -0.320 V versus AgCl/Ag; a very small cathodic peak was also detected. The SWV calibration plot was established to be linear in the range 5.0x10-6 to 9.0x10-6 mol L-1; this corresponded to a detection limit of 3.5x10-8 mol L-1. This electroanalytical method was used to monitor the decrease of molinate concentration in river waters along a biodegradation process using a bacterial mixed culture. The results achieved with this voltammetric method were compared with those obtained by use of a chromatographic method (HPLC–UV) and no significant statistical differences were observed.

DNA-based biosensor for the electrocatalytic determination of antioxidant capacity in beverages

Reactive oxygen species (ROS) are produced as a consequence of normal aerobic metabolism and are able to induce DNA oxidative damage. At the cellular level, the evaluation of the protective effect of antioxidants can be achieved by examining the integrity of the DNA nucleobases using electrochemical techniques. Herein, the use of an adenine-rich oligonucleotide (dA21) adsorbed on carbon paste electrodes for the assessment of the antioxidant capacity is proposed. The method was based on the partial damage of a DNA layer adsorbed on the electrode surface by OH• radicals generated by Fenton reaction and the subsequent electrochemical oxidation of the intact adenine bases to generate an oxidation product that was able to catalyze the oxidation of NADH. The presence of antioxidant compounds scavenged hydroxyl radicals leaving more adenines unoxidized, and thus, increasing the electrocatalytic current of NADHmeasured by differential pulse voltammetry (DPV). Using ascorbic acid (AA) as a model antioxidant species, the detection of as low as 50nMof AA in aqueous solution was possible. The protection efficiency was evaluated for several antioxidant compounds. The biosensor was applied to the determination of the total antioxidant capacity (TAC) in beverages.

Evaluation of the total antioxidant capacity of flavored water and electrochemical purine damage by sulfate radicals using a purine-based sensor

In this study, a method for the electrochemical quantification of the total antioxidant capacity (TAC) in beverages was developed. The method is based on the oxidative damage to the purine bases, adenine or guanine, that are immobilized on a glassy carbon electrode (GCE) surface. The oxidative lesions on the DNA bases were promoted by the sulfate radical generated by the persulfate/iron(II) system. The presence of antioxidants on the reactive system promoted the protection of the DNA bases immobilized on the GCE by scavenging the sulfate radical. Square-wave voltammetry (SWV) was the electrochemical technique used to perform this study. The efficiencies of five antioxidants (ascorbic acid, gallic acid, caffeic acid, coumaric acid and resveratrol) in scavenging the sulfate radical and, therefore, their ability to protect the purine bases immobilized on the GCE were investigated. These results demonstrated that the purine-based biosensor is suitable for the rapid assessment of the TAC in flavors and flavored water.

Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes

Amulti-residue methodology based on a solid phase extraction followed by gas chromatography–tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC–MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness.

Optical fiber sensor for Hg(II) based on carbon dots

An optical fiber sensor for Hg(II) in aqueous solution based on sol–gel immobilized carbon dots nanoparticles functionalized with PEG200 and N-acetyl-l-cysteine is described. This sol–gel method generated a thin (about 750 nm), homogenous and smooth (roughness of 2.7±0.7 a˚ ) filmthat immobilizes the carbon dots and allows reversible sensing of Hg(II) in aqueous solution. A fast (less than 10 s), reversible and stable (the fluorescence intensity measurements oscillate less than 1% after several calibration cycles) sensor system was obtained. The sensor allow the detection of submicron molar concentrations of Hg(II) in aqueous solution. The fluorescence intensity of the immobilized carbon dots is quenched by the presence of Hg(II) with a Stern-Volmer constant (pH = 6.8) of 5.3×105M−1.

FIA potentiometric system based on periodate polymeric membrane sensors for the assessment of ascorbic acid in commercial drinks

Ascorbic acid is found in many food samples. Its clinical and technological importance demands an easyto- use, rapid, robust and inexpensive method of analysis. For this purpose, this work proposes a new flow procedure based on the oxidation of ascorbic acid by periodate. A new potentiometric periodate sensor was constructed to monitor this reaction. The selective membranes were of PVC with porphyrin-based sensing systems and a lipophilic cation as additive. The sensor displayed a near-Nernstian response for periodate over 1.0x10-2–6.0x10-6 M, with an anionic slope of 73.9 ± 0.9 mV decade-1. It was pH independent in acidic media and presented good selectivity features towards several inorganic anions. The flow set-up operated in double-channel, carrying a 5.0x10-4 M IO- 4 solution and a suitable buffer; these were mixed in a 50-cm reaction coil. The overall flow rate was 7 ml min-1 and the injection volume 70 µl. Under these conditions, a linear behaviour against concentration was observed for 17.7–194.0 µg ml-1, presenting slopes of 0.169 mV (mg/l)-1, a reproducibility of ±1.1 mV (n = 5), and a sampling rate of ~96 samples h-1. The proposed method was applied to the analysis of beverages and pharmaceuticals.

A new MILP based approach for unit commitment in power production planning

This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

Development of a simple analytical method for the simultaneousdetermination of paracetamol, paracetamol-glucuronide andp-aminophenol in river water

Paracetamol is among the most worldwide consumed pharmaceuticals. Although its occurrence in the environment is well documented, data about the presence of its metabolites and transformation products is very scarce. The present work describes the development of an analytical method for the simultaneous determination of paracetamol, its principal metabolite (paracetamol-glucuronide) and its main transformation product (p-aminophenol) based on solid phase extraction (SPE) and high performance liquid chromatography coupled to diode array detection (HPLC-DAD). The method was applied to analysis of river waters, showing to be suitable to be used in routine analysis. Different SPE sorbents were compared and the use of two Oasis WAX cartridges in tandem proved to be the most adequate approach for sample clean up and pre-concentration. Under optimized conditions, limits of detection in the range 40–67 ng/L were obtained, as well as mean recoveries between 60 and 110% with relative standard deviations (RSD) below 6%. Finally, the developed SPE-HPLC/DAD method was successfully applied to the analysis of the selected compounds in samples from seven rivers located in the north of Portugal. Nevertheless all the compounds were detected, it was the first time that paracetamol-glucuronide was found in river water at concentrations up to 3.57 μg/L.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Uncertainty assessment approach for composite structures based on global sensitivity indices

The problem of uncertainty propagation in composite laminate structures is studied. An approach based on the optimal design of composite structures to achieve a target reliability level is proposed. Using the Uniform Design Method (UDM), a set of design points is generated over a design domain centred at mean values of random variables, aimed at studying the space variability. The most critical Tsai number, the structural reliability index and the sensitivities are obtained for each UDM design point, using the maximum load obtained from optimal design search. Using the UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on supervised evolutionary learning. Finally, using the developed ANN a Monte Carlo simulation procedure is implemented and the variability of the structural response based on global sensitivity analysis (GSA) is studied. The GSA is based on the first order Sobol indices and relative sensitivities. An appropriate GSA algorithm aiming to obtain Sobol indices is proposed. The most important sources of uncertainty are identified.

WCET analysis considering contention on memory bus in COTS-based multicores

The usage of COTS-based multicores is becoming widespread in the field of embedded systems. Providing realtime guarantees at design-time is a pre-requisite to deploy real-time systems on these multicores. This necessitates the consideration of the impact of the contention due to shared low-level hardware resources on the Worst-Case Execution Time (WCET) of the tasks. As a step towards this aim, this paper first identifies the different factors that make the WCET analysis a challenging problem in a typical COTS-based multicore system. Then, we propose and prove, a mathematically correct method to determine tight upper bounds on the WCET of the tasks, when they are co-scheduled on different cores.

Response time analysis of COTS-Based multicores considering the contention on the shared memory bus

The current industry trend is towards using Commercially available Off-The-Shelf (COTS) based multicores for developing real time embedded systems, as opposed to the usage of custom-made hardware. In typical implementation of such COTS-based multicores, multiple cores access the main memory via a shared bus. This often leads to contention on this shared channel, which results in an increase of the response time of the tasks. Analyzing this increased response time, considering the contention on the shared bus, is challenging on COTS-based systems mainly because bus arbitration protocols are often undocumented and the exact instants at which the shared bus is accessed by tasks are not explicitly controlled by the operating system scheduler; they are instead a result of cache misses. This paper makes three contributions towards analyzing tasks scheduled on COTS-based multicores. Firstly, we describe a method to model the memory access patterns of a task. Secondly, we apply this model to analyze the worst case response time for a set of tasks. Although the required parameters to obtain the request profile can be obtained by static analysis, we provide an alternative method to experimentally obtain them by using performance monitoring counters (PMCs). We also compare our work against an existing approach and show that our approach outperforms it by providing tighter upper-bound on the number of bus requests generated by a task.