Combining sampling, profiling, remote sensing and modelling to efficiently monitoring estuarine and coastal water quality

Monitoring of coastal and estuarine water quality has been traditionally performed by sampling with subsequent laboratory analysis. This has the disadvantages of low spatial and temporal resolution and high cost. In the last decades two alternative techniques have emerged to overcome this drawback: profiling and remote sensing. Profiling using multi-parameter sensors is now in a commercial stage. It can be used, tied to a boat, to obtain a quick “picture” of the system. The spatial resolution thus increases from single points to a line coincident with the boat track. The temporal resolution however remains unchanged since campaigns and resources involved are basically the same. The need for laboratory analysis was reduced but not eliminated because parameters like nutrients, microbiology or metals are still difficult to obtain with sensors and validation measurements are still needed. In the last years the improvement in satellite resolution has enabled its use for coastal and estuarine water monitoring. Although spatial coverage and resolution of satellite images in the present is already suitable to coastal and estuarine monitoring, temporal resolution is naturally limited to satellite passages and cloud cover. With this panorama the best approach to water monitoring is to integrate and combine data from all these sources. The natural tools to perform this integration are numerical models. Models benefit from the different sources of data to obtain a better calibration. After calibration they can be used to extend spatially and temporally the methods resolution. In Algarve (South of Portugal) a monitoring effort using this approach is being undertaken. The monitoring effort comprises five different locations including coastal waters, estuaries and coastal lagoons. The objective is to establish the base line situation to evaluate the impact of Waste Water Treatment Plants design and retrofitting. The field campaigns include monthly synoptic profiling, using an YSI 6600 multi-parameter system, laboratory analysis and fixed stations. The remote sensing uses ENVISAT\MERIS Level 2 Full Resolution data. This data is combined and used with the MOHID modelling system to obtain an integrate description of the systems. The results show the limitations of each method and the ability of the modelling system to integrate the results and to produce a comprehensive picture of the system.

Multi-scale keypoints in V1 and face detection

End-stopped cells in cortical area V1, which combine out- puts of complex cells tuned to different orientations, serve to detect line and edge crossings (junctions) and points with a large curvature. In this paper we study the importance of the multi-scale keypoint representa- tion, i.e. retinotopic keypoint maps which are tuned to different spatial frequencies (scale or Level-of-Detail). We show that this representation provides important information for Focus-of-Attention (FoA) and object detection. In particular, we show that hierarchically-structured saliency maps for FoA can be obtained, and that combinations over scales in conjunction with spatial symmetries can lead to face detection through grouping operators that deal with keypoints at the eyes, nose and mouth, especially when non-classical receptive field inhibition is employed. Al- though a face detector can be based on feedforward and feedback loops within area V1, such an operator must be embedded into dorsal and ventral data streams to and from higher areas for obtaining translation-, rotation- and scale-invariant face (object) detection.

Integration of numerical models in geographic databases: the case of Sado estuary management

Geographic information systems (GIS) are now widely applied in coastal resource management. Their ability to organise and interface information from a large range of public and private data sources, and their ability to combine this information, using management criteria, to develop a comprehensive picture of the system explains the success of GIS in this area. The use of numerical models as a tool to improve coastal management is also widespread. Less usual is a GIS-based management to ol implementing a comprehensive management model and integrating a numerical modelling system into itself. In this paper such a methodology is proposed. A GIS-based management tool based on the DPSIR model is presented. An overview of the MOHID numerical modelling system is given and the method of integrating this model in the management tool is described. This system is applied to the Sado Estuary (Portugal). Some preliminary results of the integration are presented, demonstrating the capabilities of the management system.

IB-DFE receiver techniques for CP-assisted block transmission within DS-CDMA and MC-CDMA systems

MC-CDMA (MultiCarrier Code Division Multiple Access), currently regarded as a promissing multiple access scheme for broadband communications, is known to combine the advantages of an OFDM-based (Orthogonal Frequency Division Multiplexing), CP-assisted (Cyclic Prefix) block transmission with those of CDMA systems. Recently, it was recognised that DS-CDMA (Direct Sequence) implementations can also take advantage of the beneficts of the CP-assisted block transmission approach, therefore enabling an efficient use of FFT-based (Fast Fourier Transform), chip level FDE (Frequency- Domain Equalisation) techniques. In this paper we consider the use of IB-DFE (Iterative Block Decision Feedback Equalisation) FDE techniques within both CP-assisted MC-CDMA systems with frequency-domain spreading and DS-CDMA systems. Our simulation results show that an IB-DFE receiver with moderate complexity is suitable in both cases, with excellent performances that can be close to the single-code matched filter bound (especially for the CP-assisted DSCDMA alternative), even with full code usage.

SIC and PIC multiuser detection for prefix-assisted DS-CDMA systems

In this paper we present iterative frequency-domain multiuser detection (MUD) receivers for the uplink transmission of direct sequence code division multiple access systems (DS-CDMA) that combine iterative block decision feedback equalization (IB-DFE) principles with interference cancelation techniques. Both successive interference cancelation (SIC) and parallel interference cancelation (PIC) structures are considered. Our performance results show that the proposed receiver structures have excellent bit error rate (BER) performances, that can be close to the single-user matched filter bound (MFB), even for fully loaded systems and severely time-dispersive channels1.

Non-linear analysis of piezolaminated structures

In the recent years the study of smart structures has attracted significant researchers, due to their potential benefits in a wide range of applications, such as shape control, vibration suppression, noise attenuation and damage detection. The applications in aerospace industry are of great relevance, such as in active control of airplane wings, helicopter blade rotor, space antenna. The use of smart materials, such as piezoelectric materials, in the form of layers or patches embedded and/or surface bonded on laminated composite structures, can provide structures that combine the superior mechanical properties of composite materials and the capability to sense and adapt their static and dynamic response, becoming adaptive structures. The piezoelectric materials have the property of generate electrical charge under mechanical load or deformation, and the reverse, applying an electrical field to the material results in mechanical strain or stresses.

Integrated multi-scale architecture of the cortex with application to computer vision

Tese de dout., Engenharia Electrónica e de Computadores, Faculdade de Ciência e Tecnologia, Universidade do Algarve, 2007

Optimised search heuristics: combining metaheuristics and exact methods to solve scheduling problems

Tese dout., Matemática, Investigação Operacional, Universidade do Algarve, 2009

Automatic tuning of PID controllers using a neuro-genetic system

Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller turning problems. In this paper we propose to combine its joint use, by exploiting the nonlinear mapping capabilites of neural networks to model objective functions, and to use them to supply their values to a genetic algorithm which performs on-line minimization.

Creativity, innovation and collaborative organizations

This article intends to make a contribution to the clarification of the concepts of creativity and innovation using a multilevel approach of individual, group and organization, in order to show that these may be better integrated within collaborative organizations. Trying to maintain the principle of the primacy of the individual (creativity) over the business (innovation), we stressed the cognitive and emotional processes (when speaking of creativity) and power and communi- cation (when it comes to innovation). Following on a description of group processes that try to combine creativity and innovation, we address the measurement of innovation, concluding with the need to avoid classifying an organization as innovative or non-innovative. The latter judgment should be left to the market itself. At the organizational level, we gave primacy to the concept of "organizational innovation", as it is within this framework that the best fusion between creativity and innovation may be achieved. Finally, we address collaboration in business as connecting people, ideas, and resources that would not normally interact with each The International Journal of Organizational Innovation Vol 5 Num 1 Summer 2012 2 other. These decentralized organizations operate in such a way that makes it possible to abolish or, at least mitigate, the role of power. We believe that this will ultimately define the future of successful organizations

Big data warehouse framework for smart revenue management

Revenue Management’s most cited definitions is probably “to sell the right accommodation to the right customer, at the right time and the right price, with optimal satisfaction for customers and hoteliers”. Smart Revenue Management (SRM) is a project, which aims the development of smart automatic techniques for an efficient optimization of occupancy and rates of hotel accommodations, commonly referred to, as revenue management. One of the objectives of this project is to demonstrate that the collection of Big Data, followed by an appropriate assembly of functionalities, will make possible to generate a Data Warehouse necessary to produce high quality business intelligence and analytics. This will be achieved through the collection of data extracted from a variety of sources, including from the web. This paper proposes a three stage framework to develop the Big Data Warehouse for the SRM. Namely, the compilation of all available information, in the present case, it was focus only the extraction of information from the web by a web crawler – raw data. The storing of that raw data in a primary NoSQL database, and from that data the conception of a set of functionalities, rules, principles and semantics to select, combine and store in a secondary relational database the meaningful information for the Revenue Management (Big Data Warehouse). The last stage will be the principal focus of the paper. In this context, clues will also be giving how to compile information for Business Intelligence. All these functionalities contribute to a holistic framework that, in the future, will make it possible to anticipate customers and competitor’s behavior, fundamental elements to fulfill the Revenue Management