Decision support system with incomplete and domain incoherent information management

Many of the most common human functions such as temporal and non-monotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This is mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems however, some systems which tried to solve the problem, have been deployed using methodologies such as production rule based expert systems, neural networks, recognition of chronicles, fuzzy expert systems, etc. SPARSE (from the Portuguese acronym, which means expert system for incident analysis and restoration support) was one of the developed systems and, in the sequence of its development, came the need to cope with incomplete and/or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA (supervisory control and data acquisition) information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the event calculus and the default reasoning rule based system paradigms, insuring soft real-time operation with incomplete, incorrect or domain incoherent information handling ability. A prototype implementation of this system is already at work in the control centre of the Portuguese Transmission Network.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Comparação de diferentes técnicas de irradiação de mama em radioterapia com recurso a acelerador linear em modo de fotões

RESUMO: Introdução – A Radioterapia (RT) é uma abordagem terapêutica para tratamento de neoplasia de mama. Contudo, diferentes técnicas de irradiação (TI) podem ser usadas. Objetivos – Comparar 4 TI, considerando a irradiação dos volumes alvo (PTV) e dos órgãos de risco (OAR). Metodologia – Selecionaram-se 7 pacientes com indicação para RT de mama esquerda. Sobre tomografia computorizada foram feitos os contornos do PTV e dos OAR. Foram calculadas 4 planimetrias/paciente para as TI: conformacional externa (EBRT), intensidade modulada com 2 (IMRT2) e 5 campos (IMRT5) e arco dinâmico (DART). Resultados – Histogramas de dose volume foram comparados para todas as TI usando o software de análise estatística, IBM SPSS v20. Com IMRT5 e DART, os OAR recebem mais doses baixas. No entanto, IMRT5 apresenta melhores índices de conformidade e homogeneidade para o PTV. Conclusões – IMRT5 apresenta o melhor índice de conformidade; EBRT e IMRT2 apresentam melhores resultados que DART. Há d.e.s entre as TI, sobretudo em doses mais baixas nos OAR.

Actuador linear para teste de teclas na indústria automóvel

As indústrias de componentes e acessórios automóveis são um elo fundamental no processo produtivo da indústria automóvel. Neste leque industrial encontra-se a Preh Portugal, Lda, como empresa fornecedora de componentes electrónicos, mais concretamente, painéis de controlo de climatização. Os painéis fornecidos pela Preh aos seus clientes encontram-se sujeitos a rigorosos testes de qualidade e funcionalidade. Neste sentido o teste funcional das teclas surge, relacionando o curso da tecla em função de uma força actuante. Esta relação está comprometida com uma curva característica padrão para o tipo de tecla. Para além destes compromissos, também é necessário que a tecla feche e abra o seu contacto eléctrico. Esta tese foca-se no desenvolvimento do teste de teclas, apresentando uma alteração ao sistema actual com a introdução de um sistema embebido, no intuito de flexibilizar o sistema de teste e reduzindo custos. O sistema embebido pretende dar capacidade de processamento ao teste e, desta forma, substituir o actual computador como elemento de processamento. A solução implementada consistiu numa mudança estrutural, através da inclusão do sistema embebido entre o computador e o sistema de deslocamento. Passando o foco central do processo de teste a residir no sistema embebido, este tem de estabelecer comunicações com os restantes elementos intervenientes no teste. Estabelece comunicações série RS-232 com o sistema de deslocamento (leitura do curso e força na tecla), Ethernet com o computador (comandos, parâmetros e resultados) e CAN com o painel de controlo de climatização (fecho/abertura do contacto eléctrico). A concretização deste projecto resultou numa nova estrutura e aplicação, a qual é facilmente integrada na linha de produção com as vantagens de ser menos onerosa e mais flexível, conforme o pretendido.

Study of the voltammetric behaviour of metam and its application to an amperometric flow system

The electrochemical behaviour of the pesticide metam (MT) at a glassy carbon working electrode (GCE) and at a hanging mercury drop electrode (HMDE) was investigated. Different voltammetric techniques, including cyclic voltammetry (CV) and square wave voltammetry (SWV), were used. An anodic peak (independent of pH) at +1.46 V vs AgCl/Ag was observed in MTaqueous solution using the GCE. SWV calibration curves were plotted under optimized conditions (pH 2.5 and frequency 50 Hz), which showed a linear response for 17–29 mg L−1. Electrochemical reduction was also explored, using the HMDE. A well defined cathodic peak was recorded at −0.72 V vs AgCl/ Ag, dependent on pH. After optimizing the operating conditions (pH 10.1, frequency 150 Hz, potential deposition −0.20 V for 10 s), calibration curves was measured in the concentration range 2.5×10−1 to 1.0 mg L−1 using SWV. The electrochemical behaviour of this compound facilitated the development of a flow injection analysis (FIA) system with amperometric detection for the quantification of MT in commercial formulations and spiked water samples. An assessment of the optimal FIA conditions indicated that the best analytical results were obtained at a potential of +1.30 V, an injection volume of 207 μL and an overall flow rate of 2.4 ml min−1. Real samples were analysed via calibration curves over the concentration range 1.3×10−2 to 1.3 mg L−1. Recoveries from the real samples (spiked waters and commercial formulations) were between 97.4 and 105.5%. The precision of the proposed method was evaluated by assessing the relative standard deviation (RSD %) of ten consecutive determinations of one sample (1.0 mg L−1), and the value obtained was 1.5%.

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.

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.

Short-term Value for the Water Stored in Headsensitivity Power System Reservoirs

As it is well known, competitive electricity markets require new computing tools for generation companies to enhance the management of its resources. The economic value of the water stored in a power system reservoir is crucial information for enhancing the management of the reservoirs. This paper proposes a practical deterministic approach for computing the short-term economic value of the water stored in a power system reservoir, emphasizing the need to considerer water stored as a scarce resource with a short-term economic value. The paper addresses a problem concerning reservoirs with small storage capacities, i.e., the reservoirs considered as head-sensitivity. More precisely, the respective hydro plant is head-dependent and a pure linear approach is unable to capture such consideration. The paper presents a case study supported by the proposed practical deterministic approach and applied on a real multi-reservoir power system with three cascaded reservoirs, considering as input data forecasts for the electric energy price and for the natural inflow into the reservoirs over the schedule time horizon. The paper presents various water schedules due to different final stored water volume conditions on the reservoirs. Also, it presents the respective economic value of the water for the reservoirs at different stored water volume conditions.

Fractional dynamics of a system with particles subjected to impacts

This paper studies the dynamics of a system composed of a collection of particles that exhibit collisions between them. Several entropy measures and different impact conditions of the particles are tested. The results reveal a Power Law evolution both of the system energy and the entropy measures, typical in systems having fractional dynamics.

Fractional discrete-time signal processing: scale conversion and linear prediction

Nonlinear Dynamics, Vol. 29

Spectral solution for the air stripping pollutants removal dynamic model with non linear steady state conditions

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.

Central nervous system involvement in Chagas' disease: an updating

A review was made of the available literature on central nervous system (CNS) involvement in Chagas' disease. Thirty-one works concerning the acute nervous form and 17 others dealing with the chronic nervous form, all presenting neuropathologic studies, were critically analysed. Based on this analysis, an attempt was made to establish the possible natural history of CNS involvement in Chagas' disease. Among others, the following facts stand out: 1) the initial, acute phase of Trypanosoma cruzi infection is usually asymptomatic and subclinical; 2) only a small percentage of cases develop encephalitis in the acute phase of Chagas' disease; 3) the symptomatic acute forms accompanied by chagasic encephalitis are grave, with death ensuing in virtually all cases as a result of the brain lesions per se or of acute chagasic myocarditis, this being usually intense and always present; 4) individuals with the asymptomatic acute form and with the mild symptomatic acute form probably have no CNS infection or, in some cases, they may have discrete encephalitis in sparse foci. In the latter case, regression of the lesions may be total, or residual inflammatory nodules of relative insignificance may persist. Thus, no anatomical basis exists that might characterize the existence of a chronic nervous form of Chagas' disease; 5) reactivation of the CNS infection in the chronic form of Chagas' disease is uncommon and occurs only in immunosuppressed patients.

Performance evaluation of a cooperative reputation system for vehicular delay-tolerant networks

In the last decade, both scientific community and automotive industry enabled communications among vehicles in different kinds of scenarios proposing different vehicular architectures. Vehicular delay-tolerant networks (VDTNs) were proposed as a solution to overcome some of the issues found in other vehicular architectures, namely, in dispersed regions and emergency scenarios. Most of these issues arise from the unique characteristics of vehicular networks. Contrary to delay-tolerant networks (DTNs), VDTNs place the bundle layer under the network layer in order to simplify the layered architecture and enable communications in sparse regions characterized by long propagation delays, high error rates, and short contact durations. However, such characteristics turn contacts very important in order to exchange as much information as possible between nodes at every contact opportunity. One way to accomplish this goal is to enforce cooperation between network nodes. To promote cooperation among nodes, it is important that nodes share their own resources to deliver messages from others. This can be a very difficult task, if selfish nodes affect the performance of cooperative nodes. This paper studies the performance of a cooperative reputation system that detects, identify, and avoid communications with selfish nodes. Two scenarios were considered across all the experiments enforcing three different routing protocols (First Contact, Spray and Wait, and GeoSpray). For both scenarios, it was shown that reputation mechanisms that punish aggressively selfish nodes contribute to increase the overall network performance.

Sparse matrix multiplication on a reconfigurable many-core architecture

Sparse matrix-vector multiplication (SMVM) is a fundamental operation in many scientific and engineering applications. In many cases sparse matrices have thousands of rows and columns where most of the entries are zero, while non-zero data is spread over the matrix. This sparsity of data locality reduces the effectiveness of data cache in general-purpose processors quite reducing their performance efficiency when compared to what is achieved with dense matrix multiplication. In this paper, we propose a parallel processing solution for SMVM in a many-core architecture. The architecture is tested with known benchmarks using a ZYNQ-7020 FPGA. The architecture is scalable in the number of core elements and limited only by the available memory bandwidth. It achieves performance efficiencies up to almost 70% and better performances than previous FPGA designs.