909 resultados para secure European System for Applications in a Multi-Vendor Environment (SESAME)


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Some patients are no longer able to communicate effectively or even interact with the outside world in ways that most of us take for granted. In the most severe cases, tetraplegic or post-stroke patients are literally `locked in` their bodies, unable to exert any motor control after, for example, a spinal cord injury or a brainstem stroke, requiring alternative methods of communication and control. But we suggest that, in the near future, their brains may offer them a way out. Non-invasive electroencephalogram (EEG)-based brain-computer interfaces (BCD can be characterized by the technique used to measure brain activity and by the way that different brain signals are translated into commands that control an effector (e.g., controlling a computer cursor for word processing and accessing the internet). This review focuses on the basic concepts of EEG-based BC!, the main advances in communication, motor control restoration and the down-regulation of cortical activity, and the mirror neuron system (MNS) in the context of BCI. The latter appears to be relevant for clinical applications in the coming years, particularly for severely limited patients. Hypothetically, MNS could provide a robust way to map neural activity to behavior, representing the high-level information about goals and intentions of these patients. Non-invasive EEG-based BCIs allow brain-derived communication in patients with amyotrophic lateral sclerosis and motor control restoration in patients after spinal cord injury and stroke. Epilepsy and attention deficit and hyperactive disorder patients were able to down-regulate their cortical activity. Given the rapid progression of EEG-based BCI research over the last few years and the swift ascent of computer processing speeds and signal analysis techniques, we suggest that emerging ideas (e.g., MNS in the context of BC!) related to clinical neuro-rehabilitation of severely limited patients will generate viable clinical applications in the near future.

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We have designed, built, and tested an early prototype of a novel subxiphoid access system intended to facilitate epicardial electrophysiology, but with possible applications elsewhere in the body. The present version of the system consists of a commercially available insertion needle, a miniature pressure sensor and interconnect tubing, read-out electronics to monitor the pressures measured during the access procedure, and a host computer with user-interface software. The nominal resolution of the system is <0.1 mmHg, and it has deviations from linearity of <1%. During a pilot series of human clinical studies with this system, as well as in an auxiliary study done with an independent method, we observed that the pericardial space contained pressure-frequency components related to both the heart rate and respiratory rate, while the thorax contained components related only to the respiratory rate, a previously unobserved finding that could facilitate access to the pericardial space. We present and discuss the design principles, details of construction, and performance characteristics of this system.

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The enormous amount of information generated through sequencing of the human genome has increased demands for more economical and flexible alternatives in genomics, proteomics and drug discovery. Many companies and institutions have recognised the potential of increasing the size and complexity of chemical libraries by producing large chemical libraries on colloidal support beads. Since colloid-based compounds in a suspension are randomly located, an encoding system such as optical barcoding is required to permit rapid elucidation of the compound structures. We describe in this article innovative methods for optical barcoding of colloids for use as support beads in both combinatorial and non-combinatorial libraries. We focus in particular on the difficult problem of barcoding extremely large libraries, which if solved, will transform the manner in which genomics, proteomics and drug discovery research is currently performed.

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A numeric model has been proposed to investigate the mechanical and electrical properties of a polymeric/carbon nanotube (CNT) composite material subjected to a deformation force. The reinforcing phase affects the behavior of the polymeric matrix and depends on the nanofiber aspect ratio and preferential orientation. The simulations show that the mechanical behavior of a computer generated material (CGM) depends on fiber length and initial orientation in the polymeric matrix. It is also shown how the conductivity of the polymer/CNT composite can be calculated for each time step of applied stress, effectively providing the ability to simulate and predict strain-dependent electrical behavior of CNT nanocomposites.

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Results on the use of a double a-SiC:H p-i-n heterostructure for signal multiplexing and demultiplexing applications in the visible range are presented. Pulsed monochromatic beams together (multiplexing mode), or a single polychromatic beam (demultiplexing mode) impinge on the device and are absorbed, accordingly to their wavelength. Red, green and blue pulsed input channels are transmitted together, each one with a specific transmission rate. The combined optical signal is analyzed by reading out, under different applied voltages, the generated photocurrent. Results show that in the multiplexing mode the output signal is balanced by the wavelength and transmission rate of each input channel, keeping the memory of the incoming optical carriers. In the demultiplexing mode the photocurrent is controlled by the applied voltage allowing regaining the transmitted information. A physical model supported by a numerical simulation gives insight into the device operation.

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Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

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Aims: This paper aims to address some of the main possible applications of actual Nuclear Medicine Imaging techniques and methodologies in the specific context of Sports Medicine, namely in two critical systems: musculoskeletal and cardiovascular. Discussion: At the musculoskeletal level, bone scintigraphy techniques proved to be a mean of diagnosis of functional orientation and high sensibility compared with other morphological imaging techniques in the detection and temporal evaluation of pathological situations, for instance allowing the acquisition of information of great relevance in athletes with stress fractures. On the other hand, infection/inflammation studies might be of an important added value to characterize specific situations, early diagnose of potential critical issues – so giving opportunity to precise, complete and fast solutions – while allowing the evaluation and eventual optimization of training programs. At cardiovascular system level, Nuclear Medicine had proved to be crucial in differential diagnosis between cardiac hypertrophy secondary to physical activity (the so called "athlete's heart") and hypertrophic cardiomyopathy, in the diagnosis and prognosis of changes in cardiac function in athletes, as well as in direct - and non-invasive - in vivo visualization of sympathetic cardiac innervation, something that seems to take more and more importance nowadays, namely in order to try to avoid sudden death episodes at intense physical effort. Also the clinical application of Positron Emission Tomography (PET) has becoming more and more widely recognized as promising. Conclusions: It has been concluded that Nuclear Medicine can become an important application in Sports Medicine. Its well established capabilities to early detection of processes involving functional properties allied to its high sensibility and the actual technical possibilities (namely those related with hybrid imaging, that allows to add information provided by high resolution morphological imaging techniques, such as CT and/or MRI) make it a powerful diagnostic tool, claiming to be used on an each day higher range of clinical applications related with all levels of sport activities. Since the improvements at equipment characteristics and detection levels allows the use of smaller and smaller doses, so minimizing radiation exposure it is believed by the authors that the increase of the use of NM tools in the Sports Medicine area should be considered.

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This work focuses on highly dynamic distributed systems with Quality of Service (QoS) constraints (most importantly real-time constraints). To that purpose, real-time applications may benefit from code offloading techniques, so that parts of the application can be offloaded and executed, as services, by neighbour nodes, which are willing to cooperate in such computations. These applications explicitly state their QoS requirements, which are translated into resource requirements, in order to evaluate the feasibility of accepting other applications in the system.

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Decentralised co-operative multi-agent systems are computational systems where conflicts are frequent due to the nature of the represented knowledge. Negotiation methodologies, in this case argumentation based negotiation methodologies, were developed and applied to solve unforeseeable and, therefore, unavoidable conflicts. The supporting computational model is a distributed belief revision system where argumentation plays the decisive role of revision. The distributed belief revision system detects, isolates and solves, whenever possible, the identified conflicts. The detection and isolation of the conflicts is automatically performed by the distributed consistency mechanism and the resolution of the conflict, or belief revision, is achieved via argumentation. We propose and describe two argumentation protocols intended to solve different types of identified information conflicts: context dependent and context independent conflicts. While the protocol for context dependent conflicts generates new consensual alternatives, the latter chooses to adopt the soundest, strongest argument presented. The paper shows the suitability of using argumentation as a distributed decentralised belief revision protocol to solve unavoidable conflicts.

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Multi-agent architectures are well suited for complex inherently distributed problem solving domains. From the many challenging aspects that arise within this framework, a crucial one emerges: how to incorporate dynamic and conflicting agent beliefs? While the belief revision activity in a single agent scenario is concentrated on incorporating new information while preserving consistency, in a multi-agent system it also has to deal with possible conflicts between the agents perspectives. To provide an adequate framework, each agent, built as a combination of an assumption based belief revision system and a cooperation layer, was enriched with additional features: a distributed search control mechanism allowing dynamic context management, and a set of different distributed consistency methodologies. As a result, a Distributed Belief Revision Testbed (DiBeRT) was developed. This paper is a preliminary report presenting some of DiBeRT contributions: a concise representation of external beliefs; a simple and innovative methodology to achieve distributed context management; and a reduced inter-agent data exchange format.

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Environmental concerns and the shortage in the fossil fuel reserves have been potentiating the growth and globalization of distributed generation. Another resource that has been increasing its importance is the demand response, which is used to change consumers’ consumption profile, helping to reduce peak demand. Aiming to support small players’ participation in demand response events, the Curtailment Service Provider emerged. This player works as an aggregator for demand response events. The control of small and medium players which act in smart grid and micro grid environments is enhanced with a multi-agent system with artificial intelligence techniques – the MASGriP (Multi-Agent Smart Grid Platform). Using strategic behaviours in each player, this system simulates the profile of real players by using software agents. This paper shows the importance of modeling these behaviours for studying this type of scenarios. A case study with three examples shows the differences between each player and the best behaviour in order to achieve the higher profit in each situation.

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Currently, a learning management system (LMS) plays a central role in any e-learning environment. These environments include systems to handle the pedagogic aspects of the teaching–learning process (e.g. specialized tutors, simulation games) and the academic aspects (e.g. academic management systems). Thus, the potential for interoperability is an important, although over looked, aspect of an LMS. In this paper, we make a comparative study of the interoperability level of the most relevant LMS. We start by defining an application and a specification model. For the application model, we create a basic application that acts as a tool provider for LMS integration. The specification model acts as the API that the LMS should implement to communicate with the tool provider. Based on researches, we select the Learning Tools Interoperability (LTI) from IMS. Finally, we compare the LMS interoperability level defined as the effort made to integrate the application on the study LMS.

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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e Computadores

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The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

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Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2014