A physical packing sequence algorithm for the container loading problem with static mechanical equilibrium conditions

The container loading problem (CLP) is a combinatorial optimization problem for the spatial arrangement of cargo inside containers so as to maximize the usage of space. The algorithms for this problem are of limited practical applicability if real-world constraints are not considered, one of the most important of which is deemed to be stability. This paper addresses static stability, as opposed to dynamic stability, looking at the stability of the cargo during container loading. This paper proposes two algorithms. The first is a static stability algorithm based on static mechanical equilibrium conditions that can be used as a stability evaluation function embedded in CLP algorithms (e.g. constructive heuristics, metaheuristics). The second proposed algorithm is a physical packing sequence algorithm that, given a container loading arrangement, generates the actual sequence by which each box is placed inside the container, considering static stability and loading operation efficiency constraints.

Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

HACCP numa indústria corticeira: implementação, identificação de pontos críticos e proposta de acções correctivas

Mestrado em Engenharia Química

Assigning real-time tasks on heterogeneous multiprocessors with two unrelated types of processors

A preliminary version of this paper appeared in Proceedings of the 31st IEEE Real-Time Systems Symposium, 2010, pp. 239–248.

Supporting parallelism in server-based multiprocessor systems

Developing an efficient server-based real-time scheduling solution that supports dynamic task-level parallelism is now relevant to even the desktop and embedded domains and no longer only to the high performance computing market niche. This paper proposes a novel approach that combines the constantbandwidth server abstraction with a work-stealing load balancing scheme which, while ensuring isolation among tasks, enables a task to be executed on more than one processor at a given time instant.

The utilization bound of static-priority preemptive partitioned multiprocessor scheduling is 50%

This paper studies static-priority preemptive scheduling on a multiprocessor using partitioned scheduling. We propose a new scheduling algorithm and prove that if the proposed algorithm is used and if less than 50% of the capacity is requested then all deadlines are met. It is known that for every static-priority multiprocessor scheduling algorithm, there is a task set that misses a deadline although the requested capacity is arbitrary close to 50%.

Project, modelling and simulation of air stripping columns for the treatment of groundwater contaminated with volatile organic compounds

Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for the column design for any particular type of packing and contaminant avoiding the necessity of a pre-defined diameter used in the classical approach. It also renders unnecessary the employment of the graphical Eckert generalized correlation for pressure drop estimates. The hydraulic features are previously chosen as a project criterion and only afterwards the mass transfer phenomena are incorporated, in opposition to conventional approach. The design procedure was translated into a convenient algorithm using C++ as programming language. A column was built in order to test the models used either in the design or in the simulation of the column performance. The experiments were fulfilled using a solution of chloroform in distilled water. Another model was built to simulate the operational performance of the column, both in steady state and in transient conditions. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting system of ODE can be solved, allowing for the calculation of the concentration profile in both phases inside the column. In transient state the system of PDE was numerically solved by finite differences, after a previous linearization.

Practical software improve design and performance of a randomly packed air stripping column for removing volatile organic compounds from water

STRIPPING is a software application developed for the automatic design of a randomly packing column where the transfer of volatile organic compounds (VOCs) from water to air can be performed and to simulate it’s behaviour in a steady-state. This software completely purges any need of experimental work for the selection of diameter of the column, and allows a choice, a priori, of the most convenient hydraulic regime for this type of operation. It also allows the operator to choose the model used for the calculation of some parameters, namely between the Eckert/Robbins model and the Billet model for estimating the pressure drop of the gaseous phase, and between the Billet and Onda/Djebbar’s models for the mass transfer. Illustrations of the graphical interface offered are presented.

A New Approach in the Design of Air Stripping Columns for the Treatment of Groundwater Contaminated With Volatile Organic Compounds

Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for column design for any type of packing and contaminant which avoids the necessity of an arbitrary chosen diameter. It also avoids the employment of the usual graphical Eckert correlations for pressure drop. The hydraulic features are previously chosen as a project criterion. The design procedure was translated into a convenient algorithm in C++ language. A column was built in order to test the design, the theoretical steady-state and dynamic behaviour. The experiments were conducted using a solution of chloroform in distilled water. The results allowed for a correction in the theoretical global mass transfer coefficient previously estimated by the Onda correlations, which depend on several parameters that are not easy to control in experiments. For best describe the column behaviour in stationary and dynamic conditions, an original mathematical model was developed. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting ODE can be solved by analytical methods, and in dynamic state the discretization of the PDE by finite differences allows for the overcoming of this difficulty. To estimate the contaminant concentrations in both phases in the column, a numerical algorithm was used. The high number of resulting algebraic equations and the impossibility of generating a recursive procedure did not allow the construction of a generalized programme. But an iterative procedure developed in an electronic worksheet allowed for the simulation. The solution is stable only for similar discretizations values. If different values for time/space discretization parameters are used, the solution easily becomes unstable. The system dynamic behaviour was simulated for the common liquid phase perturbations: step, impulse, rectangular pulse and sinusoidal. The final results do not configure strange or non-predictable behaviours.

CPMD-mindful task assignment for NPS-F

The multiprocessor scheduling scheme NPS-F for sporadic tasks has a high utilisation bound and an overall number of preemptions bounded at design time. NPS-F binpacks tasks offline to as many servers as needed. At runtime, the scheduler ensures that each server is mapped to at most one of the m processors, at any instant. When scheduled, servers use EDF to select which of their tasks to run. Yet, unlike the overall number of preemptions, the migrations per se are not tightly bounded. Moreover, we cannot know a priori which task a server will be currently executing at the instant when it migrates. This uncertainty complicates the estimation of cache-related preemption and migration costs (CPMD), potentially resulting in their overestimation. Therefore, to simplify the CPMD estimation, we propose an amended bin-packing scheme for NPS-F allowing us (i) to identify at design time, which task migrates at which instant and (ii) bound a priori the number of migrating tasks, while preserving the utilisation bound of NPS-F.

As newsletters com vídeos incorporados como instrumento de comunicação. O caso da clínicas Persona

Dissertação de Mestrado apresentada ao Instituto Superior de Contabilidade e Administração do Porto, para obtenção do grau de Mestre em Marketing Digital, sob orientação da Prof. Sandrina Teixeira

Inspeção, Diagnóstico e Reparação de Estruturas de Betão Armado

O mercado da reabilitação de estruturas em Portugal está em voga, sendo um nicho de mercado com evolução galopante nos últimos anos fruto da consciencialização das entidades responsáveis, assim como das necessidades de intervir no parque edificado cada vez mais degradado, resultando num estímulo para o mercado da construção face ao seu estado atual. As causas associadas à degradação prematura dos materiais estruturais resultam de erros de conceção e execução, assim como do facto de muitas estruturas de betão armado do parque habitacional edificado nas décadas de 60 e 70, estarem a atingir o fim do seu período de vida útil. Na avaliação do estado de degradação de estruturas de betão armado aconselha-se a utilização de ensaios não destrutivos, uma vez que permitem efetuar um diagnóstico com resultados positivos salvaguardando a integridade da estrutura. A norma EN 1504“Produtos e Sistemas para a proteção e reparação de estruturas de betão” estipula os procedimentos de execução, as características dos materiais mais adequados a cada tipo de projeto, assim como a divisão do seu encadeamento em 5 fases. O caso prático apresentado é um edifício de prestação de serviços municipais, tendo sido aplicado com o maior rigor possível as fases de inspeção, diagnóstico, deliberação e reparação. Foi efetuada uma fase de diagnóstico, de carácter visual assim como de caracterização física dos elementos estruturais em betão armado através de ensaios “in situ”. A estrutura avaliada apresenta debilidades e um estado de degradação acelerado, pelo que urge uma intervenção de reparação por forma a repor a estrutura com as características da sua conceção, salvaguardando a segurança das pessoas e bens.

Energy-aware task mapping onto heterogeneous platforms using DVFS and sleep states

Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.

P-SOCRATES: A parallel software framework for time-critical many-core systems

Article in Press, Corrected Proof

Algoritmo genético para empacotamento de contentores

No âmbito da investigação operacional o problema de empacotamento de contentores é conhecido por procurar definir uma configuração de carga, de forma a otimizar a utilização de um espaço disponível para efetuar o empacotamento. Este problema pode ser apresentado em diversas formas, formas estas que variam em função das características de cada empacotamento. Estas características podem ser: o tipo de carga que se pretende carregar (homogénea ou heterogénea), a possibilidade de a carga poder sofrer rotações em todas as suas dimensões ou apenas em algumas, o lucro que está associado a cada caixa carregada ou restrições inerentes ao contentor como por exemplo dimensões. O interesse pelo estudo de problemas de empacotamento de contentores tem vindo a receber cada vez mais ênfase por várias razões, uma delas é o interesse financeiro dado que o transporte é uma prática que representa custos, sendo importante diminuir estes custos aproveitando o volume do contentor da melhor forma. Outra preocupação que motiva o estudo deste problema prende-se com fatores ambientes, onde se procura racionalizar os recursos naturais estando esta também ligada a questões financeiras. Na literatura podem ser encontradas varias propostas para solucionar este problema, cada uma destas dirigidas a uma variante do problema, estas propostas podem ser determinísticas ou não determinísticas onde utilizam heurísticas ou metaheurísticas. O estudo realizado nesta dissertação descreve algumas destas propostas, nomeadamente as metaheurísticas que são utilizadas na resolução deste problema. O trabalho aqui apresentado traz também uma nova metaheurísticas, mais precisamente um algoritmo genético que terá como objetivo, apresentar uma configuração de carga para um problema de empacotamento de um contentor. O algoritmo genético tem como objetivo a resolução do seguinte problema: empacotar várias caixas retangulares com diversos tamanhos num contentor. Este problema é conhecido como Bin-Packing. A novidade que este algoritmo genético vai introduzir nas diversas soluções apresentadas até à data, é uma nova forma de criar padrões iniciais, ou seja, é utilizada a heurística HSSI (Heurística de Suavização de Superfícies Irregulares) que tem como objetivo criar uma população inicial de forma a otimizar o algoritmo genético. A heurística HSSI tenta resolver problemas de empacotamento simulando, o comportamento da maioria das pessoas ao fazer este processo na vida real, contudo, tem um campo de busca reduzido entre as soluções possíveis e será então utilizado um algoritmo genético para ampliar este campo de busca e explorar novas soluções. No final pretende-se obter um software onde será possível configurar um dado problema de empacotamento de um contentor e obter, a solução do mesmo através do algoritmo genético. Assim sendo, o estudo realizado tem como principal objetivo contribuir com pesquisas e conclusões, sobre este problema e trazer uma nova proposta de solução para o problema de empacotamento de contentores.