A performance lower bound for quadratic timing recovery accounting for the symbol transition density

The symbol transition density in a digitally modulated signal affects the performance of practical synchronization schemes designed for timing recovery. This paper focuses on the derivation of simple performance limits for the estimation of the time delay of a noisy linearly modulated signal in the presence of various degrees of symbol correlation produced by the varioustransition densities in the symbol streams. The paper develops high- and low-signal-to-noise ratio (SNR) approximations of the so-called (Gaussian) unconditional Cramér–Rao bound (UCRB),as well as general expressions that are applicable in all ranges of SNR. The derived bounds are valid only for the class of quadratic, non-data-aided (NDA) timing recovery schemes. To illustrate the validity of the derived bounds, they are compared with the actual performance achieved by some well-known quadratic NDA timing recovery schemes. The impact of the symbol transitiondensity on the classical threshold effect present in NDA timing recovery schemes is also analyzed. Previous work on performancebounds for timing recovery from various authors is generalized and unified in this contribution.

A programming environment having three levels of complexity for mobile robotics = Entorno de programación con tres niveles de complejidad para robótica móvil

This paper presents a programming environment for supporting learning in STEM, particularly mobile robotic learning. It was designed to maintain progressive learning for people with and without previous knowledge of programming and/or robotics. The environment was multi platform and built with open source tools. Perception, mobility, communication, navigation and collaborative behaviour functionalities can be programmed for different mobile robots. A learner is able to programme robots using different programming languages and editor interfaces: graphic programming interface (basic level), XML-based meta language (intermediate level) or ANSI C language (advanced level). The environment supports programme translation transparently into different languages for learners or explicitly on learners’ demand. Learners can access proposed challenges and learning interfaces by examples. The environment was designed to allow characteristics such as extensibility, adaptive interfaces, persistence and low software/hardware coupling. Functionality tests were performed to prove programming environment specifications. UV BOT mobile robots were used in these tests

A Sequential Allocation Problem: The Asymptotic Distribution of Resources

In this paper we consider a sequential allocation problem with n individuals. The first individual can consume any amount of some endowment leaving the remaining for the second individual, and so on. Motivated by the limitations associated with the cooperative or non-cooperative solutions we propose a new approach. We establish some axioms that should be satisfied, representativeness, impartiality, etc. The result is a unique asymptotic allocation rule. It is shown for n = 2; 3; 4; and a claim is made for general n. We show that it satisfies a set of desirable properties. Key words: Sequential allocation rule, River sharing problem, Cooperative and non-cooperative games, Dictator and ultimatum games. JEL classification: C79, D63, D74.

Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One interesting alternative for solving this limitation is the use of PGL+, a possibilistic logic over Gödel logic extended with fuzzy constants. Fuzzy constants in PGL+ allow expressing disjunctive information about the unknown value of a variable, in the sense of a magnitude, modelled as a (unary) predicate. The aim of this article is twofold: firstly, we formalize DePGL+, a possibilistic defeasible logic programming language that extends P-DeLP through the use of PGL+ in order to incorporate fuzzy constants and a fuzzy unification mechanism for them. Secondly, we propose a way to handle conflicting arguments in the context of the extended framework.

A logic programming framework for possibilistic argumentation: formalization and logical properties

In the last decade defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning. The logic programming paradigm has shown to be particularly useful for developing different argument-based frameworks on the basis of different variants of logic programming which incorporate defeasible rules. Most of such frameworks, however, are unable to deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper presents Possibilistic Logic Programming (P-DeLP), a new logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty. Such features are formalized on the basis of PGL, a possibilistic logic based on G¨odel fuzzy logic. One of the applications of P-DeLP is providing an intelligent agent with non-monotonic, argumentative inference capabilities. In this paper we also provide a better understanding of such capabilities by defining two non-monotonic operators which model the expansion of a given program P by adding new weighed facts associated with argument conclusions and warranted literals, respectively. Different logical properties for the proposed operators are studied

Trust region versus line search for computing the optical flow

We consider the numerical treatment of the optical flow problem by evaluating the performance of the trust region method versus the line search method. To the best of our knowledge, the trust region method is studied here for the first time for variational optical flow computation. Four different optical flow models are used to test the performance of the proposed algorithm combining linear and nonlinear data terms with quadratic and TV regularization. We show that trust region often performs better than line search; especially in the presence of non-linearity and non-convexity in the model.

Sierpinski curve Julia sets for quadratic rational maps

We investigate under which dynamical conditions the Julia set of a quadratic rational map is a Sierpiński curve.

Treatment of micropollutants in municipal wastewater: study of a sequential batch biofilter

All the experimental part of this final project was done at Laboratoire de Biotechnologie Environnementale (LBE) from the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, during 6 months (November 2013- May 2014). A fungal biofilter composed of woodchips was designed in order to remove micropollutants from the effluents of waste water treatment plants. Two fungi were tested: Pleurotus ostreatus and Trametes versicolor in order to evaluate their efficiency for the removal of two micropollutants: the anti-inflammatory drug naproxen and the antibiotic sulfamethoxazole,. Although Trametes versicolor was able to degrade quickly naproxen, this fungus was not any more active after one week of operation in the filter. Pleurotus ostreatus was, on contrary, able to survive more than 3 months in the filter, showing good removal efficiencies of naproxen and sulfamethoxazole during all this period, in tap water but also in real treated municipal wastewater. Several other experiments have provided insight on the removal mechanisms of these micropollutants in the fungal biofilter (degradation and adsorption) and also allowed to model the removal trend. Fungal treatment with Pleurotus ostreatus grown on wood substrates appeared to be a promising solution to improve micropollutants removal in wastewater.

A Virtual Laboratory Structure for Developing Programming Labs

Virtual Laboratories are an indispensablespace for developing practical activities in a Virtual Environment. In the field of Computer and Software Engineering different types of practical activities have tobe performed in order to obtain basic competences which are impossible to achieve by other means. This paper specifies an ontology for a general virtual laboratory.The proposed ontology provides a mechanism to select the best resources needed in a Virtual Laboratory once a specific practical activity has been defined and the maincompetences that students have to achieve in the learning process have been fixed. Furthermore, the proposed ontology can be used to develop an automatic and wizardtool that creates a Moodle Classroom using the practical activity specification and the related competences.

Combining Generic Programming and Service-Oriented Architectures for the Effective and Timely Development of Complex e-Learning Systems

Peer-reviewed

Programming and analysing measurement experiments using the PicoCricket system

The aim of this project is to get used to another kind of programming. Since now, I used very complex programming languages to develop applications or even to program microcontrollers, but PicoCricket system is the evidence that we don’t need so complex development tools to get functional devices. PicoCricket system is the clear example of simple programming to make devices work the way we programmed it. There’s an easy but effective way to programs mall devices just saying what we want them to do. We cannot do complex algorithms and mathematical operations but we can program them in a short time. Nowadays, the easier and faster we produce, the more we earn. So the tendency is to develop fast, cheap and easy, and PicoCricket system can do it.