Object transportation by multiple mobile robots controlled by attractor dynamics: theory and implementation

Dynamical systems theory is used as a theoretical language and tool to design a distributed control architecture for teams of mobile robots, that must transport a large object and simultaneously avoid collisions with (either static or dynamic) obstacles. Here we demonstrate in simulations and implementations in real robots that it is possible to simplify the architectures presented in previous work and to extend the approach to teams of n robots. The robots have no prior knowledge of the environment. The motion of each robot is controlled by a time series of asymptotical stable states. The attractor dynamics permits the integration of information from various sources in a graded manner. As a result, the robots show a strikingly smooth an stable team behaviour.

Scheduling a cutting and treatment stainless steel sheet line with self-management capabilities

With advancement in computer science and information technology, computing systems are becoming increasingly more complex with an increasing number of heterogeneous components. They are thus becoming more difficult to monitor, manage, and maintain. This process has been well known as labor intensive and error prone. In addition, traditional approaches for system management are difficult to keep up with the rapidly changing environments. There is a need for automatic and efficient approaches to monitor and manage complex computing systems. In this paper, we propose an innovative framework for scheduling system management by combining Autonomic Computing (AC) paradigm, Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems

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.

On-line self-healing of circuits implemented on reconfigurable FPGAs

To boost logic density and reduce per unit power consumption SRAM-based FPGAs manufacturers adopted nanometric technologies. However, this technology is highly vulnerable to radiation-induced faults, which affect values stored in memory cells, and to manufacturing imperfections. Fault tolerant implementations, based on Triple Modular Redundancy (TMR) infrastructures, help to keep the correct operation of the circuit. However, TMR is not sufficient to guarantee the safe operation of a circuit. Other issues like module placement, the effects of multi- bit upsets (MBU) or fault accumulation, have also to be addressed. In case of a fault occurrence the correct operation of the affected module must be restored and/or the current state of the circuit coherently re-established. A solution that enables the autonomous restoration of the functional definition of the affected module, avoiding fault accumulation, re-establishing the correct circuit state in real-time, while keeping the normal operation of the circuit, is presented in this paper.

O uso das redes sociais no recrutamento externo em empresas portuguesas

Este estudo tem como objetivo explorar o papel das redes sociais nos processos de recrutamento das organizações portuguesas. Em específico, procura identificar os motivos que levam as organizações a recrutar através da internet e dos meios on-line ao dispor, nomedamente através das Redes Socais na Internet (RSIs), as vantagens e desvantagens da sua utilização comparativamente com os métodos tradicionais. Para a realização do estudo foram selecionadas 5 empresas portuguesas que utilizam as redes sociais on-line para divulgar as suas ofertas de emprego, atrair e recrutar talentos. Foi utilizada a metodologia qualitativa, optando-se pelo estudo caso múltiplo e exploratório. O instrumento de recolha de informação foi a entrevista semiestruturada. Integraram este estudo 5 empresas de distintas áreas de negócio e com a sua sede no distrito do Porto. No total, foram realizadas 5 entrevistas, uma a cada responsável pelos recursos humanos ou recrutamento das empresas em estudo. Um desses responsáveis é, simultaneamente, o gerente da empresa. Os resultados sugerem que as empresas portuguesas, de forma gradual, começam a aceder cada vez mais às redes sociais para apoiar os seus processos de recrutamento. No entanto, essa técnica de recrutamento ainda não é utilizada de forma isolada nem substitui os métodos tradicionais de recrutamento. Na parte final da dissertação são discutidos os principais resultados obtidos e apresentadas as conclusões do estudo aqui levado a cabo.

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.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Multiple Roots of Systems of Equations by Repulsion Merit Functions

In this paper we address the problem of computing multiple roots of a system of nonlinear equations through the global optimization of an appropriate merit function. The search procedure for a global minimizer of the merit function is carried out by a metaheuristic, known as harmony search, which does not require any derivative information. The multiple roots of the system are sequentially determined along several iterations of a single run, where the merit function is accordingly modified by penalty terms that aim to create repulsion areas around previously computed minimizers. A repulsion algorithm based on a multiplicative kind penalty function is proposed. Preliminary numerical experiments with a benchmark set of problems show the effectiveness of the proposed method.

A comunicação on-line das ONGs e a angariação de fundos

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Marketing Digital, sob orientação da Mestre Inês Veiga Pereira “Esta versão contém as críticas e sugestões dos elementos do júri”

Strategic Drivers for Implementing Sustainability Programs in Portuguese Organizations– Let’s Listen to Aristotle: From Triple to Quadruple Bottom Line

This article describes a study that investigated the main strategic drivers that influence the implementation of sustainability/social responsibility programs. An online survey was administered to managers of Portuguese organizations with certified management systems. The findings suggest that the implementation of such programs is mainly correlated to: 1.) the approach to understanding and working toward the satisfaction of the community’s needs (in the broad sense of social responsibility); 2.) how systematically sustainability within the organization is identified and managed (e.g., pollution prevention, improved environmental performance, and compliance with the applicable environmental laws); and 3.) the degree to which the organization tries to understand the needs of the employees and works toward satisfying them. In addition to the survey, five interviews with top managers of the surveyed organizations provided some useful insights. There was no consensus on the meaning of sustainability and social responsibility: some described it as an instrumental approach for obtaining better organizational results, while others regarded it as the right thing to do (i.e., it is values driven). In all cases, however, the managers supported a kind of umbrella construct under which different size corporations use different models (for example, the Dow Jones Sustainability Index (DJSI), Global Reporting Initiative (GRI), ISO 14001 environmental management systems), although some managers reported that they simply do not know what to do. All of those surveyed agreed that the lack of a systematic approach could represent a major threat to their organization, making them willing to pay more attention and take more action on the issue of sustainability. An additional suggestion made by managers was to change from a triple bottom line (economic dimension, environmental dimension, social equity dimension) to a quadruple bottom line by adding another dimension: personal and family happiness. This fourth dimension was recognized by the Greek philosopher/thinker Aristotle (384-322 BCE) who thought of happiness as the highest good (virtue) and ultimate goal and purpose of life, achieved through living well, in harmony. Such harmony suggests a balance and a lack of excess—in other words a sustainable existence.

Multi-Objective and Financial Portfolio Optimization of Carrier-Sense Multiple Access Protocols with Cooperative Diversity

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.

Power Law Behavior and Self-similarity in Modern Industrial Accidents

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.

Coordinated Maneuver for Gradient Search Using Multiple AUV's

OCEANS 2003. Proceedings (Volume:1 )

Hybrid Maneuver for Gradient Search with Multiple Coordinated AUVs

This work presents a hybrid maneuver for gradient search with multiple AUV's. The mission consists in following a gradient field in order to locate the source of a hydrothermal vent or underwater freshwater source. The formation gradient search exploits the environment structuring by the phenomena to be studied. The ingredients for coordination are the payload data collected by each vehicle and their knowledge of the behaviour of other vehicles and detected formation distortions.

Response Time Analysis for Fixed-Priority Tasks with Multiple Probabilistic Parameters

Demo presented in 12th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2015). 8 to 12, Jun, 2015. La Roche-en-Ardenne, Belgium. Extended abstract.