Proposta de um método probabilístico de estimativa de custos de construção.

Projetos de construção são caracterizados pela escala, complexidade e seus riscos. Não é incomum encontrar planejamento e definição de escopo incompletos o que leva a aumento de custos e prazos. O objetivo desse trabalho é descrever um método de avaliação de riscos de forma a aumentar a previsibilidade da estimativa de custos do empreendimento. Para isso foram utilizados conceitos de gerenciamento de projetos, de simulação e de analise de riscos descritos na literatura para a constituição de um método de análise de riscos em estimativa de custos. A aplicação do método proposto em comparação com o método tradicional traz vantagens no que diz respeito à abrangência da análise. Enquanto pelo método tradicional a análise do empreendimento se faz por meio de suas tarefas, o método proposto analisa de forma distinta o planejamento do empreendimento nas suas três dimensões fundamentais: escopo, prazo e custo.

1-3 Piezocomposite design optimised for high frequency kerfless transducer arrays

Piezocomposites that can operate at frequencies above 30 MHz without spurious modes are required in order to develop sufficiently sensitive high frequency arrays for high resolution imaging. However, scaling down of conventional piezocomposite fabrication techniques becomes increasingly difficult as dimensions decrease with increasing frequency. The approach presented here is to use micro-moulded 1-3 piezocomposites and a distribution of piezoelectric segment size and separation. Innovative approaches to composite pattern design, based on a randomized spatial distribution, are presented. Micro-moulding techniques are shown to be suitable for fabricating composites with dimensions required for high frequency composites. Randomized piezocomposite patterns are modeled and are shown to suppress spurious modes.

Perceptual learning, roving and the unsupervised bias

Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when . certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervised neural network models can cope easily with roving conditions. What makes humans so inferior compared to these models? As experimental and conceptual work has shown, human perceptual learning is neither supervised nor unsupervised but reward-based learning. Reward-based learning suffers from the so-called unsupervised bias, i.e., to prevent synaptic " drift" , the . average reward has to be exactly estimated. However, this is impossible when two or more stimulus types with different rewards are presented during training (and the reward is estimated by a running average). For this reason, we propose no learning occurs in roving conditions. However, roving hinders perceptual learning only for combinations of similar stimulus types but not for dissimilar ones. In this latter case, we propose that a critic can estimate the reward for each stimulus type separately. One implication of our analysis is that the critic cannot be located in the visual system. © 2011 Elsevier Ltd.

Making the case for inclusive design.

This paper describes the University of Cambridge, Engineering Design Centre's (EDC) case for inclusive design, based on 10 years of research, promotion and knowledge transfer. In summary, inclusive design applies an understanding of customer diversity to inform decisions throughout the development process, in order to better satisfy the needs of more people. Products that are more inclusive can reach a wider market, improve customer satisfaction and drive business success. The rapidly ageing population increases the importance of this approach. The case presented here has helped to convince BT, Nestlé and others to adopt an inclusive approach.

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Design of diesel smoke feedback control using a combination of PI control algorithm and performance optimization

A novel smoke sensor was used to realize smoke feedback control on a diesel engine. The controller design based on a combination of PI control algorithm and the engine performance optimization is described. Experimental results demonstrate how this control system behave to meet both of the speed and smoke requirements during engine transients.

Low-bias terahertz amplitude modulator based on split-ring resonators and graphene.

Split-ring resonators represent the ideal route to achieve optical control of the incident light at THz frequencies. These subwavelength metamaterial elements exhibit broad resonances that can be easily tuned lithographically. We have realized a design based on the interplay between the resonances of metallic split rings and the electronic properties of monolayer graphene integrated in a single device. By varying the major carrier concentration of graphene, an active modulation of the optical intensity was achieved in the frequency range between 2.2 and 3.1 THz, achieving a maximum modulation depth of 18%, with a bias as low as 0.5 V.

Terahertz optical modulator based on metamaterial split-ring resonators and graphene

The integration of quantum cascade lasers with devices capable of efficiently manipulating terahertz light represents a fundamental step for many different applications. Split-ring resonators, subwavelength metamaterial elements exhibiting broad resonances that are easily tuned lithographically, represent the ideal route to achieve such optical control of the incident light. We have realized a design based on the interplay between metallic split rings and the electronic properties of a graphene monolayer integrated into a single device. By acting on the doping level of graphene, an active modulation of the optical intensity was achieved in the frequency range between 2.2 and 3.1 THz, with a maximum modulation depth of 18%. © 2014 Society of Photo-Optical Instrumentation Engineers.

Graphene-based optical modulator realized in metamaterial split-ring resonators operating in the THz frequency range

The integration of quantum cascade lasers with devices capable of efficiently manipulating terahertz light, represents a fundamental step for many different applications. Split-ring resonators, sub-wavelength metamaterial elements exhibiting broad resonances that are easily tuned lithographically, represent the ideal route to achieve such optical control of the incident light. We have realized a design based on the interplay between metallic split rings and the electronic properties of a graphene monolayer integrated into a single device. By acting on the doping level of graphene, an active modulation of the optical intensity was achieved in the frequency range between 2.2 THz and 3.1 THz, with a maximum modulation depth of 18%.

Learning and Example Selection for Object and Pattern Detection

This thesis presents a learning based approach for detecting classes of objects and patterns with variable image appearance but highly predictable image boundaries. It consists of two parts. In part one, we introduce our object and pattern detection approach using a concrete human face detection example. The approach first builds a distribution-based model of the target pattern class in an appropriate feature space to describe the target's variable image appearance. It then learns from examples a similarity measure for matching new patterns against the distribution-based target model. The approach makes few assumptions about the target pattern class and should therefore be fairly general, as long as the target class has predictable image boundaries. Because our object and pattern detection approach is very much learning-based, how well a system eventually performs depends heavily on the quality of training examples it receives. The second part of this thesis looks at how one can select high quality examples for function approximation learning tasks. We propose an {em active learning} formulation for function approximation, and show for three specific approximation function classes, that the active example selection strategy learns its target with fewer data samples than random sampling. We then simplify the original active learning formulation, and show how it leads to a tractable example selection paradigm, suitable for use in many object and pattern detection problems.

Staged Competence Learning in Developmental Robotics

M.H. Lee, Q. Meng and F. Chao, 'Staged Competence Learning in Developmental Robotics', Adaptive Behavior, 15(3), pp 241-255, 2007. the full text will be available in September 2008

Teaching Crossroads: 11th IPB Erasmus Week

In the wake of the latest news regarding IPB’s award for best Polytechnic Institute in Portugal, we would like to congratulate the IPB community who has always striven for the quality of the institution within the national and international academic milieu. We are, undoubtedly, bowled over by the 1st place in the national context (out of the 27 national institutions under evaluation) and the 7th position in the international scope. In fact, it is worth mentioning that the IPB has won this award, three years in a row, being in a leading position in the ranking promoted and sponsored by the European Union. This year’s edition has selected and evaluated over 1300 world higher education institutions. Teaching Crossroads intends thus to give a watershed contribution to the IPB’s successful and most valued pathway. Numbers indicate that Teaching Crossroads has had over 2550 downloads since it first came out. But let’s cut to the chase. Once again, we are delighted to present the 5th number of Teaching Crossroads. This wholly calculated and well-sustained editorial adventure started in 2012 when the first number of Teaching Crossroads first saw the light. This year’s publication includes the areas of Human Geography/anthropology, Information Technology and Forensics and Language and culture, focusing on minority languages. Alongside this, as in the two last previous numbers, we’ve included the specific area for International mobility, Intensive Programmes and Erasmus+ Mobility of Individuals, being the latter financed by the European Union within the Erasmus+ Programme, whereas the former is sponsored uniquely by the foreign partner institution, in this case, Lillebaelt Academy in Denmark. These types of programmes convey very positive and overarching ideas, resonant in cross-cultural and educational benefits, valuable for all the involved partners. We would very kindheartedly like to thank the authors for having contributed with much enlightening and serious articles on a wide array of areas. Pablo M. Orduna Pórtus’s article focuses on border culture and heritage management. The author’s study is placed on two borderlands of the Iberian Peninsula: Roncal Valley (Navarre) and Riverbanks of Douro. Going beyond the linear or physical conception of the border, the author centres his study on the metaphysical and symbolic ideas of the frontier that sustain his anthropological analysis. Michal Popdora manages to find evidence for his proposal of a new conception of teaching Image Processing, based on the student-centered approach. A hands-on experience on a Project-based Learning methodology sustains the teaching project. Grounded on “a forensic-flavored style”, using the author’s own words, he shows how students can become engaged in a highly effective learning process. Cláudia Martins is already a confirmed habitué of this publication, as in every Erasmus Week she delivers a lecture on Portuguese language and culture to visiting teaching and non-teaching staff. This time, the author decided to delve into a Portugal’s official language, Mirandese, spoken in a small designated area in the northeastern part of Portugal, Miranda do Douro and its surrounding area. The author gives account of some thought-provoking facts about the language, from the origin and the survival of the language, however still a minority language, up to the moment when it was acknowledged Portugal’s second official language, together with the challenges that nowadays faces. Luís Frölen Ribeiro, João Eduardo Ribeiro, Carlos Casimiro Costa, António Duarte, Carlos Andrade from the Polytechnic Institute and Arne Svinth, John Madsen, Morten Thomsen, Kent Smidstrup, Carsten John Jacobsen from the Lillebaelt Academy, in Denmark, participate in a joint project which they describe, outlining the main goals and gains of the project. To overcome teaching difficulties regarding the engineering degrees, a 12-ECTS joint course from Lillebaelt Academy and Polytechnic Institute of Bragança was created based on the Danish model. The course Product Development and Industrial Processing was hence created. Rui Pedro Lopes presents an insightful and acute account of the Internationalization programmes in Higher Education in Europe. At one go, the author describes his own experience as a visiting lecturer, within the Erasmus+ programme, to Università Politecnica delle Marche in Ancona, Italy, in a Master’s degree in computer science, bringing to light a personal reflection on the goals and benefits of the mobility for both students and teachers. Finally, the author puts forth some suggestions that would improve the whole mobility process. We sincerely hope to have stimulated you to keep on reading, upholding the belief that these texts can represent valuable sources for both teachers and students in their research work.

Learning Unions of Rectangles with Queries

We investigate the efficient learnability of unions of k rectangles in the discrete plane (1,...,n)[2] with equivalence and membership queries. We exhibit a learning algorithm that learns any union of k rectangles with O(k^3log n) queries, while the time complexity of this algorithm is bounded by O(k^5log n). We design our learning algorithm by finding "corners" and "edges" for rectangles contained in the target concept and then constructing the target concept from those "corners" and "edges". Our result provides a first approach to on-line learning of nontrivial subclasses of unions of intersections of halfspaces with equivalence and membership queries.

Effectiveness of Loss labeling in Improving TCP Performance in Wired/Wireless Networks

The current congestion-oriented design of TCP hinders its ability to perform well in hybrid wireless/wired networks. We propose a new improvement on TCP NewReno (NewReno-FF) using a new loss labeling technique to discriminate wireless from congestion losses. The proposed technique is based on the estimation of average and variance of the round trip time using a filter cal led Flip Flop filter that is augmented with history information. We show the comparative performance of TCP NewReno, NewReno-FF, and TCP Westwood through extensive simulations. We study the fundamental gains and limits using TCP NewReno with varying Loss Labeling accuracy (NewReno-LL) as a benchmark. Lastly our investigation opens up important research directions. First, there is a need for a finer grained classification of losses (even within congestion and wireless losses) for TCP in heterogeneous networks. Second, it is essential to develop an appropriate control strategy for recovery after the correct classification of a packet loss.

A pll based frequency synthesizer in 0.13 um sige bicmos for mb-ofdm uwb systems

With the growing demand for high-speed and high-quality short-range communication, multi-band orthogonal frequency division multiplexing ultra-wide band (MB-OFDM UWB) systems have recently garnered considerable interest in industry and in academia. To achieve a low-cost solution, highly integrated transceivers with small die area and minimum power consumption are required. The key building block of the transceiver is the frequency synthesizer. A frequency synthesizer comprised of two PLLs and one multiplexer is presented in this thesis. Ring oscillators are adopted for PLL implementation in order to drastically reduce the die area of the frequency synthesizer. The poor spectral purity appearing in the frequency synthesizers involving mixers is greatly improved in this design. Based on the specifications derived from application standards, a design methodology is presented to obtain the parameters of building blocks. As well, the simulation results are provided to verify the performance of proposed design.