13 resultados para Olive industry
em Universidade do Minho
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Dissertação de mestrado em Bioengenharia
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During recent decades it has been possible to identify several problems in construction industry project management, related with to systematic failures in terms of fulfilling its schedule, cost and quality targets, which highlight a need for an evaluation of the factors that may cause these failures. Therefore, it is important to understand how project managers plan the projects, so that the performance and the results can be improved. However, it is important to understand if other areas beyond cost and time management that are mentioned on several studies as the most critical areas, receive the necessary attention from construction project managers. Despite the cost and time are the most sensitive areas/fields, there are several other factors that may lead to project failure. This study aims at understand the reasons that may cause the deviation in terms of cost, time and quality, from the project management point of view, looking at the knowledge areas mentioned by PMI (Project Management Institute).
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Although most of the accidents occurred in Olive Oil Mill (OOM) resulted from “basic” risks, there is a need to apply adequate tools to support risk decisions that can meet the specificities of this sector. This study aims to analyse the views of Occupational, Safety & Health (OSH) practitioners about the risk assessment process in OOM, identifying the key difficulties inherent to the risk assessment process in these sector, as well as identifying some improvements to the current practice. This analysis was based on a questionnaire that was developed and applied to 13 OSH practitioners working at OOM. The results showed that the time available to perform the risk assessment is the more frequent limitation. They believe that the methodologies available are not an important limitation to this process. However, a specific risk assessment methodology, that includes acceptance criteria adjusted to the OOM reality, using risk metrics supported on the frequency of accidents and workdays lost, were indicated as being also an important contributions improve the process. A semi-quantitative approach, complemented with the use of the sector accident statistics, can be a good solution for this sector. However, further strategies should also be adopted, mainly those that can lead to an easy application of the risk assessment process.
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Nowadays, organizations are increasingly looking to invest in business intelligence solutions, mainly private companies in order to get advantage over its competitors, however they do not know what is necessary. Business intelligence allows an analysis of consolidated information in order to obtain more specific outlets and certain indications in order to support the decision making process. You can take the right decision based on the data collected from different information systems present in the organization and outside of them. The textile sector is a sector where concept of Business Intelligence it is not many explored yet. Actually there are few textile companies that have a BI platform. Thus, the article objective is present an architecture and show all the steps by which companies need to spend to implement a successful free homemade Business Intelligence system. As result the proposed approach it was validated using real data aiming assess the steps defined.
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During the recent years followed by the Global Financial Crisis (GFC), most of business and industries around the globe have been hardly hit to the limit that it still struggling to survive, suffering from the crisis financial consequences. For instance, in the construction industry; many construction projects have been suspended or totally cancelled. Nevertheless, among this dilemma, a call has been raised to use the sustainable practices to mitigate the effects of the GFC on construction industry. For the first look, it seems that there is contradiction since the sustainable solutions are often associated with an increase in the initial cost, undoubtedly, the sustainable practices have many advantages in both economic and environment aspects, however, the question which needs to be addressed here is, to what extent using such sustainable practices can mitigate the negative effects of the economic downturn on construction industry. Therefore, it is a challenging argument for using such sustainable construction from its economic perspective, however, this paper is aiming to present the economical benefits of sustainable practices in construction industry, and trying to clear the doubt of the high initial costs of the sustainable construction through studying the life cycle benefit of green building.
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Olive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14±2 to 25±6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.
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Dissertação de mestrado integrado em Engenharia e Gestão Industrial
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Proceedings da AUTEX 2015, Bucareste, Roménia.
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ICEIM – International Conference in Entrepreneurship and Innovation Management, Roma, 17-18 de setembro de 2015.
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Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.
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Olive mill wastewaters (OMW) and vinasses (VS) are effluents produced respectively by olive mills and wineries, both sectors are of great economic importance in Mediterranean countries. These effluents cause a large environmental impact, when not properly processed, due to their high concentration of phenolic compounds, COD and colour. OMW may be treated by biological processes but, in this case, a dilution is necessary, increasing water consumption. The approach here in proposed consists on the bioremediation of OMW and VS by filamentous fungi. In a screening stage, three fungi (Aspergillus ibericus, Aspergillus uvarum, Aspergillus niger) were selected to bioremediate undiluted OMW, two-fold diluted OMW supplemented with nutrients, and a mixture of OMW and VS in the proportion 1:1 (v/v). Higher reductions of phenolic compounds, colour and COD were achieved mixing both residues; with A. uvarum providing the best results. In addition, the production of enzymes was also evaluated during this bioremediation process, detecting in all cases lipolytic, proteolytic and tannase activities. A. ibericus, A. uvarum and A. niger achieved the highest value of lipase (1253.7 ± 161.2 U/L), protease (3700 ± 124.3 U/L) and tannase (284.4 ± 12.1 U/L) activities, respectively. Consequently, this process is an interesting alternative to traditional processes to manage these residues, providing simultaneously high economic products, which can be employed in the same industries.
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Biofilms in food processing plants represent not only a problem to human health but also cause economic losses by technical failure in several systems. In fact, many foodborne outbreaks have been found to be associated with biofilms. Biofilms may be prevented by regular cleaning and disinfection, but this does not completely prevent biofilm formation. Besides, due to their diversity and to the development of specialized phenotypes, it is well known that biofilms are more resistant to cleaning and disinfection than planktonic microorganisms. In recent years, a considerable effort has been made in the prevention of microbial adhesion and biofilm formation on food processing surfaces and novel technologies have been introduced. In this context, this chapter discusses the main conventional and emergent strategies that have been employed to prevent bacterial adhesion to food processing surfaces and thus to efficiently maintain good hygiene throughout the food industries.
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The prelims comprise: * Half-Title Page * Dedication Page * Title Page * Copyright Page * Table of Contents * Foreword * Acknowledgements * Disclaimer * Introduction