Dynamic adaptation of stability periods for service level agreements

A QoS adaptation to dynamically changing system conditions that takes into consideration the user’s constraints on the stability of service provisioning is presented. The goal is to allow the system to make QoS adaptation decisions in response to fluctuations in task traffic flow, under the control of the user. We pay special attention to the case where monitoring the stability period and resource load variation of Service Level Agreements for different types of services is used to dynamically adapt future stability periods, according to a feedback control scheme. System’s adaptation behaviour can be configured according to a desired confidence level on future resource usage. The viability of the proposed approach is validated by preliminary experiments.

Classification of some penalty methods

Optimization problems arise in science, engineering, economy, etc. and we need to find the best solutions for each reality. The methods used to solve these problems depend on several factors, including the amount and type of accessible information, the available algorithms for solving them, and, obviously, the intrinsic characteristics of the problem. There are many kinds of optimization problems and, consequently, many kinds of methods to solve them. When the involved functions are nonlinear and their derivatives are not known or are very difficult to calculate, these methods are more rare. These kinds of functions are frequently called black box functions. To solve such problems without constraints (unconstrained optimization), we can use direct search methods. These methods do not require any derivatives or approximations of them. But when the problem has constraints (nonlinear programming problems) and, additionally, the constraint functions are black box functions, it is much more difficult to find the most appropriate method. Penalty methods can then be used. They transform the original problem into a sequence of other problems, derived from the initial, all without constraints. Then this sequence of problems (without constraints) can be solved using the methods available for unconstrained optimization. In this chapter, we present a classification of some of the existing penalty methods and describe some of their assumptions and limitations. These methods allow the solving of optimization problems with continuous, discrete, and mixing constraints, without requiring continuity, differentiability, or convexity. Thus, penalty methods can be used as the first step in the resolution of constrained problems, by means of methods that typically are used by unconstrained problems. We also discuss a new class of penalty methods for nonlinear optimization, which adjust the penalty parameter dynamically.

Improvement of a filters method in a derivative free optimization

Constraints nonlinear optimization problems can be solved using penalty or barrier functions. This strategy, based on solving the problems without constraints obtained from the original problem, have shown to be e ective, particularly when used with direct search methods. An alternative to solve the previous problems is the lters method. The lters method introduced by Fletcher and Ley er in 2002, , has been widely used to solve problems of the type mentioned above. These methods use a strategy di erent from the barrier or penalty functions. The previous functions de ne a new one that combine the objective function and the constraints, while the lters method treat optimization problems as a bi-objective problems that minimize the objective function and a function that aggregates the constraints. Motivated by the work of Audet and Dennis in 2004, using lters method with derivative-free algorithms, the authors developed works where other direct search meth- ods were used, combining their potential with the lters method. More recently. In a new variant of these methods was presented, where it some alternative aggregation restrictions for the construction of lters were proposed. This paper presents a variant of the lters method, more robust than the previous ones, that has been implemented with a safeguard procedure where values of the function and constraints are interlinked and not treated completely independently.

Self-Scheduling for energy and spinning reserve of wind/CSP plants by a MILP approach

This paper is on the self-scheduling for a power producer taking part in day-ahead joint energy and spinning reserve markets and aiming at a short-term coordination of wind power plants with concentrated solar power plants having thermal energy storage. The short-term coordination is formulated as a mixed-integer linear programming problem given as the maximization of profit subjected to technical operation constraints, including the ones related to a transmission line. Probability density functions are used to model the variability of the hourly wind speed and the solar irradiation in regard to a negative correlation. Case studies based on an Iberian Peninsula wind and concentrated solar power plants are presented, providing the optimal energy and spinning reserve for the short-term self-scheduling in order to unveil the coordination benefits and synergies between wind and solar resources. Results and sensitivity analysis are in favour of the coordination, showing an increase on profit, allowing for spinning reserve, reducing the need for curtailment, increasing the transmission line capacity factor. (C) 2014 Elsevier Ltd. All rights reserved.

Project scheduling under multiple resources constraints using a genetic algorithm

The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Hyperspectral unmixing based on mixtures of Dirichlet components

This paper introduces a new unsupervised hyperspectral unmixing method conceived to linear but highly mixed hyperspectral data sets, in which the simplex of minimum volume, usually estimated by the purely geometrically based algorithms, is far way from the true simplex associated with the endmembers. The proposed method, an extension of our previous studies, resorts to the statistical framework. The abundance fraction prior is a mixture of Dirichlet densities, thus automatically enforcing the constraints on the abundance fractions imposed by the acquisition process, namely, nonnegativity and sum-to-one. A cyclic minimization algorithm is developed where the following are observed: 1) The number of Dirichlet modes is inferred based on the minimum description length principle; 2) a generalized expectation maximization algorithm is derived to infer the model parameters; and 3) a sequence of augmented Lagrangian-based optimizations is used to compute the signatures of the endmembers. Experiments on simulated and real data are presented to show the effectiveness of the proposed algorithm in unmixing problems beyond the reach of the geometrically based state-of-the-art competitors.

Novel techniques for the design and practical realization of switched-capacitor circuits in deep-submicron CMOS technologies

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Scheduling of a hydro producer considering head-dependency, price scenarios and risk-aversion

In this paper, a mixed-integer quadratic programming approach is proposed for the short-term hydro scheduling problem, considering head-dependency, discontinuous operating regions and discharge ramping constraints. As new contributions to earlier studies, market uncertainty is introduced in the model via price scenarios, and risk aversion is also incorporated by limiting the volatility of the expected profit through the conditional value-at-risk. Our approach has been applied successfully to solve a case Study based on one of the main Portuguese cascaded hydro systems, requiring a negligible computational time.

Quality indicators in the education of children with profound Intellectual and multiple disabilities

Todas as crianças, independentemente das suas necessidades, deveriam ter acesso a uma educação de qualidade e a serem incluídas nas suas famílias e comunidades. Esta afirmação inclui as crianças mais vulneráveis, em particular as crianças com dificuldades intelectuais e multideficiência. Os resultados da investigação sobre a educação de crianças com dificuldades intelectuais e multideficiência ainda não produziram até ao momento informação suficiente que possa ser usada para desenvolver indicadores de qualidade para a avaliação das práticas e dos serviços. A investigação nesta área é limitada por constrangimentos éticos, dificuldades na determinação de amostras e desafios metodológicos, sendo reduzido o número de estudos capaz de produzir a informação necessária. Este artigo tem como objetivo discutir fatores que contribuam para a qualidade do envolvimento de crianças com dificuldades intelectuais e multideficiência em atividades educativas, com base na experiência das autoras e na informação disponível que tem sido publicada sobre este assunto. Com base nesta discussão é sugerido um conjunto de indicadores que poderão ajudar os profissionais a dirigir as suas observações para a qualidade da oferta educativa e para aspetos significativos dos desempenhos das crianças quando envolvidas em atividades curriculares.

Trajectory planning of redundant manipulators using genetic algorithms

The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms are needed. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms. The results are compared with a genetic algorithm that adopts the direct kinematics. In both cases the trajectory planning is formulated as an optimization problem with constraints.

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Age constraints on the late cretaceous alkaline magmatism on the West Iberian margin

Cretaceous Research 30 (2009) 575–586

Including context in a routing algorithm for the internet of things

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Drug susceptibility of Plasmodium falciparum in the western Amazon region, state of Acre, Brazil

Field studies in the western Amazon region (state of Acre, Brazil) indicate that the 4-aminoquinolines, as well as the combined regimen with sulfadoxine-pyrimethamine, can no longer be recomended for the treatment and prophylaxis of P. falciparum infections in this region. Quinine remains an effective drug when used correctly. However, compliance problems arise due to the often occurring side-effects during a ten day regimen. Prospects of overcoming these constraints by combining a short course of quinine with other drugs are limited, because of the lack of suitable partner compounds. For this reason quinine/clindamycin appears to be a more practical therapy of P. falciparum malaria. In vitro data from this study suggest that mefloquine is another effective alternative for the treatment of falciparum malaria in this Amazon region.

Preliminary study of synthesis gas production from water electrolysis, using the ELECTROFUEL (R) concept

This paper describes preliminary work on the generation of synthesis gas from water electrolysis using graphite electrodes without the separation of the generated gases. This is an innovative process, that has no similar work been done earlier. Preliminary tests allowed to establish correlations between the applied current to the electrolyser and flow rate and composition of the generated syngas, as well as a characterisation of generated carbon nanoparticles. The obtained syngas can further be used to produce synthetic liquid fuels, for example, methane, methanol or DME (dimethyl ether) in a catalytic reactor, in further stages of a present ongoing project, using the ELECTROFUEL® concept. The main competitive advantage of this project lies in the built-in of an innovative technology product, from RE (renewable energy) power in remote locations, for example, islands, villages in mountains as an alternative for energy storage for mobility constraints.