Reabilitação térmica de fachadas

As fachadas são um elemento da envolvente que faz a interface entre o ambiente exterior e o interior. Do conjunto das suas características mais relevantes, existe uma, cuja importância tem vindo a aumentar devido à conjuntura ambiental e económica atual: o desempenho energético. Assim, é importante analisar as características do comportamento térmico dos elementos da fachada, com base na respetiva regulamentação em vigor (REH – D.L. n.º 118/2013 de 20 de Agosto) e analisar o contributo da sua eventual reabilitação para uma melhor qualidade térmica da fachada e por consequente uma melhor qualidade de conforto dos utentes do edificio, não desprezando o aspeto arquitetónico do mesmo. Esta monografia baseia-se na análise de casos práticos de diferentes soluções construtivas e avaliação das vantagens e desvantagens dos sistemas propostos, conferindo a possibilidade de optar pelo sistema mais eficaz de acordo com as necessidades exigidas. Assim, e com base no principal objetivo, que é o de melhorar o desempenho térmico das fachadas recorrendo à reabilitação, o enfoque é sobre a redução do consumo energético dos edificios, nomeadamente através do contributo térmico dos elementos das fachadas para a redução das necessidades energéticas por climatização.

Adaptive offloading for infotainment systems

Infotainment applications in vehicles are currently supported both by the in-vehicle platform, as well as by user’s smart devices, such as smartphones and tablets. More and more the user expects that there is a continuous service of applications inside or outside of the vehicle, provided in any of these devices (a simple but common example is hands-free mobile phone calls provided by the vehicle platform). With the increasing complexity of ‘apps’, it is necessary to support increasing levels of Quality of Service (QoS), with varying resource requirements. Users may want to start listening to music in the smartphone, or video in the tablet, being this application transparently ‘moved’ into the vehicle when it is started. This paper presents an adaptable offloading mechanism, following a service-oriented architecture pattern, which takes into account the QoS requirements of the applications being executed when making decisions.

System Level Simulation and Radio Resource Management for Distributed Antenna Systems with Cognitive Radio and Multi-Cell Cooperation

4th International Conference on Future Generation Communication Technologies (FGCT 2015), Luton, United Kingdom.

Efficient Legendre spectral tau algorithm for solving two-sided space-time Caputo fractional advection-dispersion equation

In this paper we present the operational matrices of the left Caputo fractional derivative, right Caputo fractional derivative and Riemann–Liouville fractional integral for shifted Legendre polynomials. We develop an accurate numerical algorithm to solve the two-sided space–time fractional advection–dispersion equation (FADE) based on a spectral shifted Legendre tau (SLT) method in combination with the derived shifted Legendre operational matrices. The fractional derivatives are described in the Caputo sense. We propose a spectral SLT method, both in temporal and spatial discretizations for the two-sided space–time FADE. This technique reduces the two-sided space–time FADE to a system of algebraic equations that simplifies the problem. Numerical results carried out to confirm the spectral accuracy and efficiency of the proposed algorithm. By selecting relatively few Legendre polynomial degrees, we are able to get very accurate approximations, demonstrating the utility of the new approach over other numerical methods.

Designing video lectures for MOOC

Educational videos differ from other teaching and learning technologies as they allow the benefit of using visual perception. Video lectures are not new to education, however with the use of innovative video technologies they can improve academic outcomes and extend the reach of education. They may offer extraordinary new experiences for higher education institutions (HEI). Through them lecturers can provide information and contents to students, and if used creatively, video lectures can become a powerful technological tool in education, inside and outside classrooms. Inside a classroom it can motivate students and improve topics’ debate and outside it is a good support for students’ self- learning. In some cases they can be used to work some subjects standing behind, but needed to support actual courses contents, that students do not remember (or were not even taught), opening an “in front to the past door” that backs students self-study. The student-educator dynamic is changing. Students are expecting exceptional instruction and educators are expecting students to be more and more well informed about subjects from online viewing.This article explores some of the potential benefits and challenges associated with the use of video lectures in the teaching and learning process at higher education. We will also discuss some thoughts and examples for the use of teaching materials to enhance student’s learning and try to understand how video can act as powerful and innovative to enlighten teaching and learning (note that unfortunately, sometimes, the opposite is happening).

Towards a Mobile Three-dimensional Modelling System for Underground Structures

Robotica 2012: 12th International Conference on Autonomous Robot Systems and Competitions April 11, 2012, Guimarães, Portugal

Six thinking hats: A novel metalearner for intelligent decision support in electricity markets

The energy sector has suffered a significant restructuring that has increased the complexity in electricity market players' interactions. The complexity that these changes brought requires the creation of decision support tools to facilitate the study and understanding of these markets. The Multiagent Simulator of Competitive Electricity Markets (MASCEM) arose in this context, providing a simulation framework for deregulated electricity markets. The Adaptive Learning strategic Bidding System (ALBidS) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM, ALBidS considers several different strategic methodologies based on highly distinct approaches. Six Thinking Hats (STH) is a powerful technique used to look at decisions from different perspectives, forcing the thinker to move outside its usual way of thinking. This paper aims to complement the ALBidS strategies by combining them and taking advantage of their different perspectives through the use of the STH group decision technique. The combination of ALBidS' strategies is performed through the application of a genetic algorithm, resulting in an evolutionary learning approach.

PIASA: A power and interference aware resource management strategy for heterogeneous workloads in cloud data centers

Cloud data centers have been progressively adopted in different scenarios, as reflected in the execution of heterogeneous applications with diverse workloads and diverse quality of service (QoS) requirements. Virtual machine (VM) technology eases resource management in physical servers and helps cloud providers achieve goals such as optimization of energy consumption. However, the performance of an application running inside a VM is not guaranteed due to the interference among co-hosted workloads sharing the same physical resources. Moreover, the different types of co-hosted applications with diverse QoS requirements as well as the dynamic behavior of the cloud makes efficient provisioning of resources even more difficult and a challenging problem in cloud data centers. In this paper, we address the problem of resource allocation within a data center that runs different types of application workloads, particularly CPU- and network-intensive applications. To address these challenges, we propose an interference- and power-aware management mechanism that combines a performance deviation estimator and a scheduling algorithm to guide the resource allocation in virtualized environments. We conduct simulations by injecting synthetic workloads whose characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our performance-enforcing strategy is able to fulfill contracted SLAs of real-world environments while reducing energy costs by as much as 21%.

A filter algorithm: comparison with NLP solvers

The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration—the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.