961 resultados para Self-Organizing Map
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This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies. (C) 2014 Elsevier Ltd. All rights reserved.
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Os programas de melhoria contínua dos processos são cada vez mais a aposta das empresas para fazer face ao mercado. Através da implementação destes programas é possível conferir simplicidade e padronização aos processos e consequentemente reduzir os custos com desperdícios internos relacionados com a qualidade dos mesmos. As ferramentas de melhoria da qualidade e as ferramentas associadas ao Lean Thinking representam um pilar importante no sucesso de qualquer programa de melhoria contínua dos processos. Estas ferramentas constituem meios úteis na análise, controlo, organização de dados importantes para a correta tomada de decisão nas organizações. O presente projeto tem como principal objetivo a conceção e implementação de um programa de melhoria da qualidade na Eurico Ferreira, S.A., tendo por base a avaliação da satisfação do cliente e a aplicação dos 5S. Neste contexto, o trabalho teve como fundamentação teórica a Gestão da Qualidade, Lean Thinking e algumas ferramentas de ambas as matérias. Posteriormente foi selecionada a área de negócio da empresa a abordar. Após a seleção, realizou-se um diagnóstico inicial do processo identificando os diversos pontos de melhoria onde foram aplicadas algumas ferramentas do Lean Thinking, nomeadamente o Value Stream Mapping e a metodologia 5S. Com a primeira foi possível construir um mapa do estado atual do processo, no qual estavam representados todos os intervenientes assim como o fluxo de materiais e de informação ao longo do processo. A metodologia 5S permitiu atuar sobre os desperdícios, identificando e implementando diversas melhorias no processo. Concluiu-se que a implementação das ferramentas contribuiu eficientemente para a melhoria contínua da qualidade nos processos, tendo sido decisão da coordenação alargar o âmbito do projeto aos restantes armazéns do centro logístico da empresa. Pode afirmar-se com recurso à satisfação do cliente expressa através da evolução favorável do Service-level agreement que as ferramentas implementadas têm gerado resultados muito positivos no curto prazo.
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Current Manufacturing Systems challenges due to international economic crisis, market globalization and e-business trends, incites the development of intelligent systems to support decision making, which allows managers to concentrate on high-level tasks management while improving decision response and effectiveness towards manufacturing agility. This paper presents a novel negotiation mechanism for dynamic scheduling based on social and collective intelligence. Under the proposed negotiation mechanism, agents must interact and collaborate in order to improve the global schedule. Swarm Intelligence (SI) is considered a general aggregation term for several computational techniques, which use ideas and inspiration from the social behaviors of insects and other biological systems. This work is primarily concerned with negotiation, where multiple self-interested agents can reach agreement over the exchange of operations on competitive resources. Experimental analysis was performed in order to validate the influence of negotiation mechanism in the system performance and the SI technique. Empirical results and statistical evidence illustrate that the negotiation mechanism influence significantly the overall system performance and the effectiveness of Artificial Bee Colony for makespan minimization and on the machine occupation maximization.
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New homoditopic bis-calix[4]arene-carbazole conjugates, armed with hydrophilic carboxylic acid functions at their lower rims, are disclosed. Evidence for their self-association in solution was gathered from solvatochromic and thermochromic studies, as well as from gel-permeation chromatography analysis. Their ability to function as highly sensitive sensors toward polar electron-deficient aromatic compounds is demonstrated.
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Power law (PL) distributions have been largely reported in the modeling of distinct real phenomena and have been associated with fractal structures and self-similar systems. In this paper, we analyze real data that follows a PL and a double PL behavior and verify the relation between the PL coefficient and the capacity dimension of known fractals. It is to be proved a method that translates PLs coefficients into capacity dimension of fractals of any real data.
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This essay offers a reflection on the concepts of identity and personal narrative, a line of argument that is closely interlaced with a subject‘s capacity to self-representation. As self-representation is necessarily composed upon remembrance processes, the question of memory as an element that directly influences the formation of an individual‘s identity becomes an emergent topic. Bearing this objective in mind, I shall highlight the notion of biographic continuity, the ability to elaborate a personal narrative, as an essential prerogative to attain a sense of identitary cohesion and coherence. On the other hand, I will argue that not only experienced memories play a key role in this process; intermediated, received narratives from the past, memories transmitted either symbolically or by elder members of the group or, what has been meanwhile termed ―postmemory‖, also influence the development of an individual‘s identitary map. This theoretical framework will be illustrated with the novel Paul Schatz im Uhrenkasten, written by German post-Holocaust author Jan Koneffke.
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With the help of a unique combination of density functional theory and computer simulations, we discover two possible scenarios, depending on concentration, for the hierarchical self-assembly of magnetic nanoparticles on cooling. We show that typically considered low temperature clusters, i.e. defect-free chains and rings, merge into more complex branched structures through only three types of defects: four-way X junctions, three-way Y junctions and two-way Z junctions. Our accurate calculations reveal the predominance of weakly magnetically responsive rings cross-linked by X defects at the lowest temperatures. We thus provide a strategy to fine-tune magnetic and thermodynamic responses of magnetic nanocolloids to be used in medical and microfluidics applications.
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The basic objective of this work is to evaluate the durability of self-compacting concrete (SCC) produced in binary and ternary mixes using fly ash (FA) and limestone filler (LF) as partial replacement of cement. The main characteristics that set SCC apart from conventional concrete (fundamentally its fresh state behaviour) essentially depend on the greater or lesser content of various constituents, namely: greater mortar volume (more ultrafine material in the form of cement and mineral additions); proper control of the maximum size of the coarse aggregate; use of admixtures such as superplasticizers. Significant amounts of mineral additions are thus incorporated to partially replace cement, in order to improve the workability of the concrete. These mineral additions necessarily affect the concrete’s microstructure and its durability. Therefore, notwithstanding the many well-documented and acknowledged advantages of SCC, a better understanding its behaviour is still required, in particular when its composition includes significant amounts of mineral additions. An ambitious working plan was devised: first, the SCC’s microstructure was studied and characterized and afterwards the main transport and degradation mechanisms of the SCC produced were studied and characterized by means of SEM image analysis, chloride migration, electrical resistivity, and carbonation tests. It was then possible to draw conclusions about the SCC’s durability. The properties studied are strongly affected by the type and content of the additions. Also, the use of ternary mixes proved to be extremely favourable, confirming the expected beneficial effect of the synergy between LF and FA. © 2015 RILEM.
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The Evidence Accumulation Clustering (EAC) paradigm is a clustering ensemble method which derives a consensus partition from a collection of base clusterings obtained using different algorithms. It collects from the partitions in the ensemble a set of pairwise observations about the co-occurrence of objects in a same cluster and it uses these co-occurrence statistics to derive a similarity matrix, referred to as co-association matrix. The Probabilistic Evidence Accumulation for Clustering Ensembles (PEACE) algorithm is a principled approach for the extraction of a consensus clustering from the observations encoded in the co-association matrix based on a probabilistic model for the co-association matrix parameterized by the unknown assignments of objects to clusters. In this paper we extend the PEACE algorithm by deriving a consensus solution according to a MAP approach with Dirichlet priors defined for the unknown probabilistic cluster assignments. In particular, we study the positive regularization effect of Dirichlet priors on the final consensus solution with both synthetic and real benchmark data.
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A correlation and predictive scheme for the viscosity and self-diffusivity of liquid dialkyl adipates is presented. The scheme is based on the kinetic theory for dense hard-sphere fluids, applied to the van der Waals model of a liquid to predict the transport properties. A "universal" curve for a dimensionless viscosity of dialkyl adipates was obtained using recently published experimental viscosity and density data of compressed liquid dimethyl (DMA), dipropyl (DPA), and dibutyl (DBA) adipates. The experimental data are described by the correlation scheme with a root-mean-square deviation of +/- 0.34 %. The parameters describing the temperature dependence of the characteristic volume, V-0, and the roughness parameter, R-eta, for each adipate are well correlated with one single molecular parameter. Recently published experimental self-diffusion coefficients of the same set of liquid dialkyl adipates at atmospheric pressure were correlated using the characteristic volumes obtained from the viscosity data. The roughness factors, R-D, are well correlated with the same single molecular parameter found for viscosity. The root-mean-square deviation of the data from the correlation is less than 1.07 %. Tests are presented in order to assess the capability of the correlation scheme to estimate the viscosity of compressed liquid diethyl adipate (DEA) in a range of temperatures and pressures by comparison with literature data and of its self-diffusivity at atmospheric pressure in a range of temperatures. It is noteworthy that no data for DEA were used to build the correlation scheme. The deviations encountered between predicted and experimental data for the viscosity and self-diffusivity do not exceed 2.0 % and 2.2 %, respectively, which are commensurate with the estimated experimental measurement uncertainty, in both cases.
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The S100 proteins are 10-12 kDa EF-hand proteins that act as central regulators in a multitude of cellular processes including cell survival, proliferation, differentiation and motility. Consequently, many S100 proteins are implicated and display marked changes in their expression levels in many types of cancer, neurodegenerative disorders, inflammatory and autoimmune diseases. The structure and function of S100 proteins are modulated by metal ions via Ca2+ binding through EF-hand motifs and binding of Zn2+ and Cu2+ at additional sites, usually at the homodimer interfaces. Ca2+ binding modulates S100 conformational opening and thus promotes and affects the interaction with p53, the receptor for advanced glycation endproducts and Toll-like receptor 4, among many others. Structural plasticity also occurs at the quaternary level, where several S100 proteins self-assemble into multiple oligomeric states, many being functionally relevant. Recently, we have found that the S100A8/A9 proteins are involved in amyloidogenic processes in corpora amylacea of prostate cancer patients, and undergo metal-mediated amyloid oligomerization and fibrillation in vitro. Here we review the unique chemical and structural properties of S100 proteins that underlie the conformational changes resulting in their oligomerization upon metal ion binding and ultimately in functional control. The possibility that S100 proteins have intrinsic amyloid-forming capacity is also addressed, as well as the hypothesis that amyloid self-assemblies may, under particular physiological conditions, affect the S100 functions within the cellular milieu.
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6th Real-Time Scheduling Open Problems Seminar (RTSOPS 2015), Lund, Sweden.
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Power law (PL) distributions have been largely reported in the modeling of distinct real phenomena and have been associated with fractal structures and self-similar systems. In this paper, we analyze real data that follows a PL and a double PL behavior and verify the relation between the PL coefficient and the capacity dimension of known fractals. It is to be proved a method that translates PLs coefficients into capacity dimension of fractals of any real data.
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Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.