Abstract
Several monitoring approaches have been used to understand the physical, chemical, and biological processes associated with coastal sewage discharges. However, these efforts have not improved the understanding of the interaction of effluent plume/coastal ocean processes. Autonomous underwater vehicles (AUVs) have already been shown to be very useful for performing high-resolution surveys of small features such as outfall plumes. Some of the advantages of these platforms include easier field logistics, low cost per deployment, good spatial coverage, sampling over repeated sections, and the ability to perform feature based or adaptive sampling. Once the data have been collected in the field, it is necessary to extrapolate from monitoring samples to unsampled locations. Geostatistics has been successfully used to obtain information; for example, regarding the spatial distribution of soil properties. Besides giving estimated values at unsampled locations, it provides a measure of the accuracy of the estimate, which is a significant advantage over traditional methods used to assess pollution. In this work, geostatistics is used to model and map the spatial distribution of temperature measurements gathered by an AUV in a sea ouffall monitoring campaign, with the aim of distinguishing the effluent plume from the receiving waters and characterizing its spatial variability in the vicinity of the discharge. The results demonstrate that this methodology can provide good estimates of the dispersion of effluent, and it is therefore very valuable in assessing the environmental impact and managing sea outfalls.

Abstract

Abstract
Ambient Assisted Living environments projects arise as technological responses of the scientific community to problems associated with the population-ageing phenomenon. In theory, these environments should allow de-localization of healthcare services delivery and management to the home, thus containing the economic and social costs associated with old age. The VirtualECare project is one of those environments, enhanced with proactive techniques for a better user experience, focused on elderly chronic patients, through the ability of constant learning and adaption based in user interaction and its contexts. This learning and, consequently, adaption needs, however, unequivocally user identification, especially in multi-user environments. Traditional identification techniques and methodologies are not suitable for these scenario since, usually, require user interaction and wireless identification technique (e.g. RFID, Bluetooth) are very exposed to personification. In order to obtain the expected results we needed a more advanced technology. One possible, appropriate and already fairly developed technique is Facial Recognition. In this paper we present the VirtualECare project approach to Facial Recognition authentication techniques its advantages, disadvantages and possible implementations paths.

Abstract
Sea port container terminals play an important role in the national and regional economy. The integrated scheduling of handling equipment has been recently investigated in literature to improve the performance of the container terminals. In this paper, an integrated scheduling of quay cranes and automated guided vehicles is formulated as a mixed integer linear programming model. This model minimizes the makespan of all the loading and unloading tasks for a set of cranes in a scheduling problem. Based on the simulated annealing (SA) algorithm, a scheduling method is proposed to solve the problem in a relatively short period of time. Comparison of the respective results of the mathematical model and the SA algorithm evidently shows acceptable performance of the proposed SA algorithm in finding good solutions for practical scheduling problems. Moreover, the effects of three cooling processes and two sets of control parameters on the best solution of the SA are investigated. © 2011 Academic Journals.

Abstract

Abstract
Customers are known as a brilliant source of knowledge for the companies, because they gain knowledge and expertise while selecting and using products or services. Customer knowledge management is a new stage of relationship management between organizations and the customers. Most of the models in the literature are focused on human resources to set up a framework to exchange knowledge with the customers. In this paper, the applicability of agent-based systems to the customer knowledge management was investigated. As a feasibility study, characteristics of the agents and their role in knowledge management systems were reviewed in advance. Then, the requirements of customer knowledge management systems were described. Finally, using an introductory model, the applicability of the intelligent agents in customer knowledge management systems were shown and discussed.