Logic-based schedulability analysis for compositional hard real-time embedded systems

Over the past decades several approaches for schedulability analysis have been proposed for both uni-processor and multi-processor real-time systems. Although different techniques are employed, very little has been put forward in using formal specifications, with the consequent possibility for mis-interpretations or ambiguities in the problem statement. Using a logic based approach to schedulability analysis in the design of hard real-time systems eases the synthesis of correct-by-construction procedures for both static and dynamic verification processes. In this paper we propose a novel approach to schedulability analysis based on a timed temporal logic with time durations. Our approach subsumes classical methods for uni-processor scheduling analysis over compositional resource models by providing the developer with counter-examples, and by ruling out schedules that cause unsafe violations on the system. We also provide an example showing the effectiveness of our proposal.

Comparison between immunomagnetic separation, coupled with immunofluorescence, and the techniques of Faust et al. and of Lutz for the diagnosis of Giardia lamblia cysts in human feces

In the present study, the performance of Immunomagnetic Separation technique, coupled with Immunofluorescence (IMS-IFA), was compared with the FAUST et al. and Lutz parasitological techniques for the detection of Giardia lamblia cysts in human feces. One hundred and twenty-seven samples were evaluated by the three techniques at the same time showing a rate of cyst detection of 27.5% by IMS-IFA and 15.7% by both Faust et al. and Lutz techniques. Data analysis showed a higher sensitivity of IMS-IFA for the detection of G. lamblia cysts in comparison with the techniques of FAUST et al. and Lutz. The use of this methodology as a routine procedure enables the processing of many samples simultaneously, in order to increase recovery rate of G. lamblia cysts and reduce the time of sample storage.

Adaptive Penalty and Barrier function based on Fuzzy Logic

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.

Development of integrated separation processes with green solvents

Dissertação para obtenção do Grau de Doutor em Química Sustentável

Alternative solvents in separation processes

Dissertation presented to obtain the Ph.D degree in Sustainable Chemistry

A proof system for lock-free concurrency

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Separation of bioactive peptides by electrodialysis with ultrafiltration membranes: membrane characteristics, ex-situ and in-situ digestion and their impact on peptide migration

Dissertation presented to Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa for obtaining the master degree in Membrane Engineering

One-pot enzymatic resolution/separation of enantiomers using green solvents

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Maintaining the correctness of transactional memory programs

Dissertação para obtenção do Grau de Doutor em Engenharia Informática

Revision based total semantics for extended normal logic programs

Dissertação para obtenção do Grau de Doutor em Matemática - Lógica e Fundamentos da Matemática

Experimental high-throughput adsorption unit for multi-evaluation of adsorbents for gas capture, storage and separation applications

Dissertação para obtenção do grau de Mestre em Engenharia Química e Bioquímica

Separation of azeotropic mixtures using high ionicity ionic liquids

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Facilitated CO2 separation membranes: mixing cyano and amino acid-based ionic liquids

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Development of new membranes based on ionic liquid materials for gas separation

In the field of energy, natural gas is an essential bridge to a clean, low carbon, renewable energy era. However, natural gas processing and transportation regulation require the removal of contaminant compounds such as carbon dioxide (CO2). Regarding clean air, the increasing atmospheric concentrations of greenhouse gases, specifically CO2, is of particular concern. Therefore, new costeffective, high performance technologies for carbon capture have been researched and the design of materials with the ability to efficiently separate CO2 from other gases is of vital importance.(...)

Machine ethics via logic programming

Machine ethics is an interdisciplinary field of inquiry that emerges from the need of imbuing autonomous agents with the capacity of moral decision-making. While some approaches provide implementations in Logic Programming (LP) systems, they have not exploited LP-based reasoning features that appear essential for moral reasoning. This PhD thesis aims at investigating further the appropriateness of LP, notably a combination of LP-based reasoning features, including techniques available in LP systems, to machine ethics. Moral facets, as studied in moral philosophy and psychology, that are amenable to computational modeling are identified, and mapped to appropriate LP concepts for representing and reasoning about them. The main contributions of the thesis are twofold. First, novel approaches are proposed for employing tabling in contextual abduction and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets. Second, a variety of LP-based reasoning features are applied to model the identified moral facets, through moral examples taken off-the-shelf from the morality literature. These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.