48 resultados para Objective Environment

em Universidade do Minho


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Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

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Nowadays, recycling has become a very important objective for the society in the scope of a closed loop product life cycle. In recent years, new recycling techniques have been developed in the area of road pavements that allow the incorporation of high percentages of reclaimed asphalt (RA) materials in recycled asphalt mixtures. The use of foamed bitumen for production of recycled asphalt mixtures is one of those techniques, which also allows the reduction of the mixing temperatures (warm mix technology). However, it is important to evaluate if this solution can maintain or improve the performance of the resulting mixtures. Thus, the main aim of the present study is to assess the performance of warm recycled asphalt mixtures incorporating foamed bitumen as the new binder and 50% RA, in comparison with a control mixture using conventional bitumen. Four mixtures have been produced with 50% RA, one of them at typical high mixing temperatures with a conventional bitumen (control mixture) and the other three with foamed bitumen at different production temperatures. These four mixtures were tested to evaluate their compactability and water sensitivity. The laboratory test results showed that the production of recycled mixtures with foamed bitumen can be reduced by 40ºC without changing the performance of the resulting mixtures.

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Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.

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Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

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This paper presents a proposal for a management model based on reliability requirements concerning Cloud Computing (CC). The proposal was based on a literature review focused on the problems, challenges and underway studies related to the safety and reliability of Information Systems (IS) in this technological environment. This literature review examined the existing obstacles and challenges from the point of view of respected authors on the subject. The main issues are addressed and structured as a model, called "Trust Model for Cloud Computing environment". This is a proactive proposal that purposes to organize and discuss management solutions for the CC environment, aiming improved reliability of the IS applications operation, for both providers and their customers. On the other hand and central to trust, one of the CC challenges is the development of models for mutual audit management agreements, so that a formal relationship can be established involving the relevant legal responsibilities. To establish and control the appropriate contractual requirements, it is necessary to adopt technologies that can collect the data needed to inform risk decisions, such as access usage, security controls, location and other references related to the use of the service. In this process, the cloud service providers and consumers themselves must have metrics and controls to support cloud-use management in compliance with the SLAs agreed between the parties. The organization of these studies and its dissemination in the market as a conceptual model that is able to establish parameters to regulate a reliable relation between provider and user of IT services in CC environment is an interesting instrument to guide providers, developers and users in order to provide services and secure and reliable applications.

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Dissertação de mestrado em Construção e Reabilitação Sustentável

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This paper analyzes the safety, environmental and occupational health of workers in the small construction industry in Brazil. In this sector there are still many unsafe practices, which are very common in small work sites. We used a qualitative approach to understand these problems by long interviews with people who work directly in small construction sites, including occupational physicians, civil engineers, safety engineers, safety technicians, general foremen, construction workers, labor unionists and auditors. This paper aims to demonstrate that the "invisibility" of the small sites workers makes them less safe and therefore more prone to accidents, also weakening their health. The results show that small constructions workers are less visible to society and supervision because of their short periods of work. Therefore, they are also uncovered to the rigorous applicability of principles of safety and accident prevention. Thus, it has been seen in this field of work a precarious application of NR - 18, which was specifically made for the construction sites and it needs simplification to meet normative characteristics of small construction sites. In the State of Rio de Janeiro, some laws on small sites were recently created and implemented. This study concludes that the rules to work are not being taken as seriously as the legislation determinates, remaining practically unknown by many professionals, from the plot command, supervisors, engineers, architects and technicians who work on construction sites. This ignorance creates space for the lack of safety and consequently to accidents, leading to by weakness in the workers health. Therefore, the work process needs to be modified, the safety regulation must be disseminated through safer practices, promoting employee health and ensure that the work of small sites can be visible, especially ensuring the construction workers health and safety.

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Dissertação de mestrado integrado em Engenharia e Gestão Industrial

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Tese de Doutoramento em Ciências da Educação (Área de Conhecimento: Educação ambiental e para a Sustentabilidade)

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Due to the fact that different injection molding conditions tailor the mechanical response of the thermoplastic material, such effect must be considered earlier in the product development process. The existing approaches implemented in different commercial software solutions are very limited in their capabilities to estimate the influence of processing conditions on the mechanical properties. Thus, the accuracy of predictive simulations could be improved. In this study, we demonstrate how to establish straightforward processing-impact property relationships of talc-filled injection-molded polypropylene disc-shaped parts by assessing the thermomechanical environment (TME). To investigate the relationship between impact properties and the key operative variables (flow rate, melt and mold temperature, and holding pressure), the design of experiments approach was applied to systematically vary the TME of molded samples. The TME is characterized on computer flow simulation outputsanddefined bytwo thermomechanical indices (TMI): the cooling index (CI; associated to the core features) and the thermo-stress index (TSI; related to the skin features). The TMI methodology coupled to an integrated simulation program has been developed as a tool to predict the impact response. The dynamic impact properties (peak force, peak energy, and puncture energy) were evaluated using instrumented falling weight impact tests and were all found to be similarly affected by the imposed TME. The most important molding parameters affecting the impact properties were found to be the processing temperatures (melt andmold). CI revealed greater importance for the impact response than TSI. The developed integrative tool provided truthful predictions for the envisaged impact properties.

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Tese de Doutoramento em Tecnologias e Sistemas de Informação.

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Information available on the mycoflora associated to ripening Italian “grana type” cheese is very poor. Recently, ochratoxin A (OTA) was detected in samples of packed grated cheese [1]; therefore, the need of information to perform a risk management was highlighted. Moreover, sterigmatocystin (STC) has been reported in cheese and it is considered an emerging problem. Despite the fact that both of them are mycotoxins included in group 2B by IARC [2,3], no European regulation exists. So, the main goal of this work is to give for the first time a general overview about Penicillia and Aspergilli growing on the surface of ripening “grana type” cheese, with particular attention on mycotoxigenic species. To perform this, in 2013 and 2014 crust samples were scratched from ripening grana cheese wheels and also Potato Dextrose Agar plates were exposed to monitor ripening house air. Then, 140 fungal isolates were randomly chosen, purified and monosporic colonies were obtained for their identification at specie level. A polyphasic approach is followed, based on morphological characterisation, toxic extrolites profiling and gene sequencing. The identification is still in progress, but the first results based on the morphological approach showed the presence of mycotoxigenic Aspergilli (Aspergillus flavus and A. versicolor) and various Penicillium species; among them Penicillium chrysogenum, P. implicatum and P. solitum were identified. Only P. chrysogenum was reported to produce the mycotoxins cyclopiazonic acid (CPA) and roquefortine-C (ROQ-C) [4]. These results will be presented and discussed. [1] A. Biancardi, R. Piro, G. Galaverna, C. Dall’Asta, "A simple and reliable liquid chromatography–tandem mass spectrometry method for determination of ochratoxin A in hard cheese" International Journal of Food Sciences and Nutrition 64 (5), 2013, 632 – 640. [2] International Agency for Research on Cancer (IARC) “IARC Monographs on the Evaluation of Carcinogenic Risks to Humans” 31, 1983, 191 – 199. [3] International Agency for Research on Cancer (IARC) “IARC Monographs on the Evaluation of carcinogenic Risks to Humans”, suppl. 7, 1987, 72. [4] J. I. Pitt, D. A. Hocking, “Fungi and Food Spoilage” 1997, 291.

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In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

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Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.

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Dissertação de mestrado em Engenharia Industrial