Bioremediation of phosphates in seawater: approach for recirculating marine aquaculture effluents

Marine Recirculating Aquaculture Systems (RAS) produce great volume of wastewater, which may be reutilized/recirculated or reutilized after undergoing different treatment/remediation methods, or partly discharged into neighbour water-bodies (DWW). Phosphates, in particular, are usually accumulated at high concentrations in DWW, both because its monitoring is not compulsory for fish production since it is not a limiting parameter, and also because there is no specific treatment so far developed to remove them, especially in what concerns saltwater effluents. As such, this work addresses two main scientific questions. One of them regards the understanding of the actual (bio)remediation methods applied to effluents produced in marine RAS, by identifying their advantages, drawbacks and gaps concerning their exploitation in saltwater effluents. The second one is the development of a new, innovative and efficient method for the treatment of saltwater effluents that potentially fulfil the gaps identified in the conventional treatments. Thereby, the aims of this thesis are: (i) to revise the conventional treatments targeting major contaminants in marine RAS effluents, with a particular focus on the bioremediation approaches already conducted for phosphates; (ii) to characterize and evaluate the potential of oyster-shell waste collected in Ria de Aveiro as a bioremediation agent of phosphates spiked into artificial saltwater, over different influencing factors (e.g., oyster-shell pre-treatment through calcination, particle size, adsorbent concentration). Despite the use of oyster-shells for phosphorous (P) removal has already been applied in freshwater, its biosorptive potential for P in saltwater was never evaluated, as far as I am aware. The results herein generated showed that NOS is mainly composed by carbonates, which are almost completely converted into lime (CaO) after calcination (COS). Such pre-treatment allowed obtaining a more reactive material for P removal, since higher removal percentages and adsorption capacity was observed for COS. Smaller particle size fractions for both NOS and COS samples also increased P removal. Kinetic models showed that NOS adsorption followed, simultaneously, Elovich and Intraparticle Difusion kinetic models, suggesting that P removal is both a diffusional and chemically rate-controlled process. The percentage of P removal by COS was not controlled by Intraparticle Diffusion and the Elovich model was the kinetic model that best fitted phosphate removal. This work demonstrated that waste oyster-shells, either NOS or COS, could be used as an effective biosorbent for P removal from seawater. Thereby, this biomaterial can sustain a cost-effective and eco-friendly bioremediation strategy with potential application in marine RAS.

An Agent-based Classification Model

The major function of this model is to access the UCI Wisconsin Breast Cancer data-set[1] and classify the data items into two categories, which are normal and anomalous. This kind of classification can be referred as anomaly detection, which discriminates anomalous behaviour from normal behaviour in computer systems. One popular solution for anomaly detection is Artificial Immune Systems (AIS). AIS are adaptive systems inspired by theoretical immunology and observed immune functions, principles and models which are applied to problem solving. The Dendritic Cell Algorithm (DCA)[2] is an AIS algorithm that is developed specifically for anomaly detection. It has been successfully applied to intrusion detection in computer security. It is believed that agent-based modelling is an ideal approach for implementing AIS, as intelligent agents could be the perfect representations of immune entities in AIS. This model evaluates the feasibility of re-implementing the DCA in an agent-based simulation environment called AnyLogic, where the immune entities in the DCA are represented by intelligent agents. If this model can be successfully implemented, it makes it possible to implement more complicated and adaptive AIS models in the agent-based simulation environment.

Human Behavious Modelling for Discrete Event and Agent Based Simulation: A Case Study

This study is about the comparison of simulation techniques between Discrete Event Simulation (DES) and Agent Based Simulation (ABS). DES is one of the best-known types of simulation techniques in Operational Research. Recently, there has been an emergence of another technique, namely ABS. One of the qualities of ABS is that it helps to gain a better understanding of complex systems that involve the interaction of people with their environment as it allows to model concepts like autonomy and pro-activeness which are important attributes to consider. Although there is a lot of literature relating to DES and ABS, we have found none that focuses on exploring the capability of both in tackling the human behaviour issues which relates to queuing time and customer satisfaction in the retail sector. Therefore, the objective of this study is to identify empirically the differences between these simulation techniques by stimulating the potential economic benefits of introducing new policies in a department store. To apply the new strategy, the behaviour of consumers in a retail store will be modelled using the DES and ABS approach and the results will be compared. We aim to understand which simulation technique is better suited to human behaviour modelling by investigating the capability of both techniques in predicting the best solution for an organisation in using management practices. Our main concern is to maximise customer satisfaction, for example by minimising their waiting times for the different services provided.

Object-Oriented Modeling Simulation and Control of Activated Sludge Process

Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.

Microstructural-based approach to the interpretation of clays and transitional soils behaviour

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2016.

Economic growth and individual satisfaction in an agent-based economy

Macro and micro-economic perspectives are combined in an eco- nomic growth model. An agent-based modeling approach is used to develop an overlapping generation framework where endogenous growth is supported by work- ers that decide to study depending on their relative (skilled and unskilled) indi- vidual satisfaction. The micro perspective is based on individual satisfaction: an utility function computed from the variation of the relative income in both space and time. The macro perspective emerges from micro decisions, and, as in other growth models of this type, concerns an important allocative social decision the share of the working population that is engaged in producing ideas (skilled work- ers). Simulations show that production and satisfaction levels are higher when the evolution of income measured in both space and time are equally weighted.

Demand and supply oriented input-output models: a linkage analysis for Portugal.

Doutoramento em Economia.

Adaptive lighting design as a holistic approach to public lighting

Dissertação para obtenção do grau de Doutor em Design, apresentada na Universidade de Lisboa - Faculdade de Arquitetura.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Internal market orientation and market/oriented behaviours

Purpose – The purpose of this empirical paper is to investigate internal marketing from a behavioural perspective. The impact of internal marketing behaviours, operationalised as an internal market orientation (IMO), on employees' marketing and other in/role behaviours (IRB) were examined. Design/methodology/approach – Survey data measuring IMO, market orientation and a range of constructs relevant to the nomological network in which they are embedded were collected from the UK retail managers. These were tested to establish their psychometric properties and the conceptual model was analysed using structural equations modelling, employing a partial least squares methodology. Findings – IMO has positive consequences for employees' market/oriented and other IRB. These, in turn, influence marketing success. Research limitations/implications – The paper provides empirical support for the long/held assumption that internal and external marketing are related and that organisations should balance their external focus with some attention to employees. Future research could measure the attitudes and behaviours of managers, employees and customers directly and explore the relationships between them. Practical implications – Firm must ensure that they do not put the needs of their employees second to those of managers and shareholders; managers must develop their listening skills and organisations must become more responsive to the needs of their employees. Originality/value – The paper contributes to the scarce body of empirical support for the role of internal marketing in services organisations. For researchers, this paper legitimises the study of internal marketing as a route to external market success; for managers, the study provides quantifiable evidence that focusing on employees' wants and needs impacts their behaviours towards the market. © 2010, Emerald Group Publishing Limited

A virtual agent to sustaining children's engagement in language learning

In this thesis we aimed to explore the potential of gamification - defined as “the use of game elements in non-game contexts” [30] - in increasing children's (aged 5 to 6) engagement with the task. This is mainly due to the fact that our world is living a technological era, and videogames are an example of this engagement by being able to maintain children’s (and adults) engagement for hours straight. For the purpose of limiting complexity, we only addressed the feedback element by introducing it with an anthropomorphic virtual agent (human-like aspect), because research shows that virtual agents (VA’s) can influence behavioural change [17], or even induce emotions on humans both through the use of feedback provided and their facial expressions, which can interpreted in the same way as of humans’ [2]. By pairing the VA with the gamification concept, we wanted to 1) create a VA that is likely to be well-received by children (appearance and behaviour), and 2) have the immediate feedback that games have, so we can give children an assessment of their actions in real-time, as opposed to waiting for feedback from someone (traditional teaching), and with this give students more chances to succeed [32, 43]. Our final system consisted on a virtual environment, where children formed words that corresponded to a given image. In order to measure the impact that the VA had on engagement, the system was developed in two versions: one version of the system was limited to provide a simple feedback environment, where the VA provided feedback, by responding with simple phrases (i.e. “correct” or “incorrect”); for the second version, the VA had a more complex approach where it tried to encourage children to complete the word – a motivational feedback - even when they weren’t succeeding. Lastly we conducted a field study with two groups of children, where one group tested the version with the simple feedback, and the other group tested the ‘motivational’ version of the system. We used a quantitative approach to analyze the collected data that measured the engagement, based on the number of tasks (words) completed and time spent with system. The results of the evaluation showed that the use of motivational feedback may carry a positive effect on engaging children.

A virtual agent to sustaining children's engagement in language learning

In this thesis we aimed to explore the potential of gamification - defined as “the use of game elements in non-game contexts” [30] - in increasing children's (aged 5 to 6) engagement with the task. This is mainly due to the fact that our world is living a technological era, and videogames are an example of this engagement by being able to maintain children’s (and adults) engagement for hours straight. For the purpose of limiting complexity, we only addressed the feedback element by introducing it with an anthropomorphic virtual agent (human-like aspect), because research shows that virtual agents (VA’s) can influence behavioural change [17], or even induce emotions on humans both through the use of feedback provided and their facial expressions, which can interpreted in the same way as of humans’ [2]. By pairing the VA with the gamification concept, we wanted to 1) create a VA that is likely to be well-received by children (appearance and behaviour), and 2) have the immediate feedback that games have, so we can give children an assessment of their actions in real-time, as opposed to waiting for feedback from someone (traditional teaching), and with this give students more chances to succeed [32, 43]. Our final system consisted on a virtual environment, where children formed words that corresponded to a given image. In order to measure the impact that the VA had on engagement, the system was developed in two versions: one version of the system was limited to provide a simple feedback environment, where the VA provided feedback, by responding with simple phrases (i.e. “correct” or “incorrect”); for the second version, the VA had a more complex approach where it tried to encourage children to complete the word – a motivational feedback - even when they weren’t succeeding. Lastly we conducted a field study with two groups of children, where one group tested the version with the simple feedback, and the other group tested the ‘motivational’ version of the system. We used a quantitative approach to analyze the collected data that measured the engagement, based on the number of tasks (words) completed and time spent with system. The results of the evaluation showed that the use of motivational feedback may carry a positive effect on engaging children.

Field-oriented assessment of agricultural crops through temporal segmentation of modis VI data.

Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.