995 resultados para Kinect sensor
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Vector sensors measure both the acoustic pressure and the three components of particle velocity. Because of this, a vector sensor array (VSA) has the advantage of being able to provide substantially higher directivity with a much smaller aperture than an array of traditional scalar (pressure only) hydrophones. Although several, most of them theoretic, works were published from early nineties, only in the last years due to improvements and availability of vector sensor technology, the interest on field experiments with VSA increased in the scientific community. During the Makai Experiment, that took place off the coast of Kauai I., Hawaii, in September 2005, real data were collected with a 4 element vertical VSA. These data will be discussed in the present paper. The acoustic signals were emitted from a near source (low frequency ship noise) and two high frequency controlled acoustic sources located within a range of 2km from the VSA. The advantages of the VSA over traditional scalar hydrophone arrays in source localization will be addressed using conventional beamforming.
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Dissolved oxygen (DO) is one of the most important environmental variables of water quality, especially for marine life. Consequently, oxygen is one of the Chemical Quality Elements required for the implementation of European Union Water Framework Directive. This study uses the example of the Ria Formosa, a meso-tidal lagoon on the south coast of Portugal to demonstrate how monitoring of water quality for coastal waters must be well designed to identify symptoms of episodic hypoxia. New data from the western end of the Ria Formosa were compared to values in a database of historical data and in the published literature to identify long-term trends. The dissolved oxygen concentration values in the database and in the literature were generally higher than those found in this study, where episodic hypoxia was observed during the summer. Analysis of the database showed that the discrepancy was probably related with the time and the sites where the samples had been collected, rather than a long-term trend. The most problematic situations were within the inner lagoon near the city of Faro, where episodic hypoxia (<2 mg dm3 DO) occurred regularly in the early morning. These results emphasise the need for a balanced sampling strategy for oxygen monitoring which includes all periods of the day and night, as well as a representative range of sites throughout the lagoon. Such a strategy would provide adequate data to apply management measures to reduce the risk of more persistent hypoxia that would impact on the ecological, important natural resource. economic and leisure uses of this important natural resource.
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Dissertação de mestrado, Engenharia Informática, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
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Dissertação de mestrado, Engenharia Informática, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
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Dissertação de Mestrado, Engenharia Informática, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
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Dissertação de Mestrado, Engenharia Informática, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015
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A novel molecularly imprinted optosensing material based on multi-walled carbon nanotube-quantum dots (MWCNT-QDs) has been designed and synthesized for its high selectivity, sensitivity and specificity in the recognition of a target protein bovine serum albumin (BSA). Molecularly imprinted polymer coated MWCNT-QDs using BSA as the template (BMIP-coated MWCNT-QDs) exhibits a fast mass-transfer speed with a response time of 25 min. It is found that the BSA as a target protein can significantly quench the luminescence of BMIP-coated MWCNT-QDs in a concentration-dependent manner that is best described by a Stem-Volmer equation. The K-SV for BSA is much higher than bovine hemoglobin and lysozyme, implying a highly selective recognition of the BMIP-coated MWCNT-QDs to BSA. Under optimal conditions, the relative fluorescence intensity of BMIP-coated MWCNT-QDs decreases linearly with the increasing target protein BSA in the concentration range of 5.0 x 10(-7)-35.0 x 10(-7) M with a detection limit of 80 nM.
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In this paper, a biosensor based on a glassy carbon electrode (GCE) was used for the evaluation of the total antioxidant capacity (TAC) of flavours and flavoured waters. This biosensor was constructed by immobilising purine bases, guanine and adenine, on a GCE. Square wave voltammetry (SWV) was selected for the development of this methodology. Damage caused by the reactive oxygen species (ROS), superoxide radical (O2·−), generated by the xanthine/xanthine oxidase (XOD) system on the DNA-biosensor was evaluated. DNA-biosensor encountered with oxidative lesion when it was in contact with the O2·−. There was less oxidative damage when reactive antioxidants were added. The antioxidants used in this work were ascorbic acid, gallic acid, caffeic acid, coumaric acid and resveratrol. These antioxidants are capable of scavenging the superoxide radical and therefore protect the purine bases immobilized on the GCE surface. The results demonstrated that the DNA-based biosensor is suitable for the rapid assess of TAC in beverages.
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Localization is a fundamental task in Cyber-Physical Systems (CPS), where data is tightly coupled with the environment and the location where it is generated. The research literature on localization has reached a critical mass, and several surveys have also emerged. This review paper contributes on the state-of-the-art with the proposal of a new and holistic taxonomy of the fundamental concepts of localization in CPS, based on a comprehensive analysis of previous research works and surveys. The main objective is to pave the way towards a deep understanding of the main localization techniques, and unify their descriptions. Furthermore, this review paper provides a complete overview on the most relevant localization and geolocation techniques. Also, we present the most important metrics for measuring the accuracy of localization approaches, which is meant to be the gap between the real location and its estimate. Finally, we present open issues and research challenges pertaining to localization. We believe that this review paper will represent an important and complete reference of localization techniques in CPS for researchers and practitioners and will provide them with an added value as compared to previous surveys.
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Secure group communication is a paradigm that primarily designates one-to-many communication security. The proposed works relevant to secure group communication have predominantly considered the whole network as being a single group managed by a central powerful node capable of supporting heavy communication, computation and storage cost. However, a typical Wireless Sensor Network (WSN) may contain several groups, and each one is maintained by a sensor node (the group controller) with constrained resources. Moreover, the previously proposed schemes require a multicast routing support to deliver the rekeying messages. Nevertheless, multicast routing can incur heavy storage and communication overheads in the case of a wireless sensor network. Due to these two major limitations, we have reckoned it necessary to propose a new secure group communication with a lightweight rekeying process. Our proposal overcomes the two limitations mentioned above, and can be applied to a homogeneous WSN with resource-constrained nodes with no need for a multicast routing support. Actually, the analysis and simulation results have clearly demonstrated that our scheme outperforms the previous well-known solutions.
RadiaLE: A framework for designing and assessing link quality estimators in wireless sensor networks
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Stringent cost and energy constraints impose the use of low-cost and low-power radio transceivers in large-scale wireless sensor networks (WSNs). This fact, together with the harsh characteristics of the physical environment, requires a rigorous WSN design. Mechanisms for WSN deployment and topology control, MAC and routing, resource and mobility management, greatly depend on reliable link quality estimators (LQEs). This paper describes the RadiaLE framework, which enables the experimental assessment, design and optimization of LQEs. RadiaLE comprises (i) the hardware components of the WSN testbed and (ii) a software tool for setting-up and controlling the experiments, automating link measurements gathering through packets-statistics collection, and analyzing the collected data, allowing for LQEs evaluation. We also propose a methodology that allows (i) to properly set different types of links and different types of traffic, (ii) to collect rich link measurements, and (iii) to validate LQEs using a holistic and unified approach. To demonstrate the validity and usefulness of RadiaLE, we present two case studies: the characterization of low-power links and a comparison between six representative LQEs. We also extend the second study for evaluating the accuracy of the TOSSIM 2 channel model.
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Radio link quality estimation in Wireless Sensor Networks (WSNs) has a fundamental impact on the network performance and also affects the design of higher-layer protocols. Therefore, for about a decade, it has been attracting a vast array of research works. Reported works on link quality estimation are typically based on different assumptions, consider different scenarios, and provide radically different (and sometimes contradictory) results. This article provides a comprehensive survey on related literature, covering the characteristics of low-power links, the fundamental concepts of link quality estimation in WSNs, a taxonomy of existing link quality estimators, and their performance analysis. To the best of our knowledge, this is the first survey tackling in detail link quality estimation in WSNs. We believe our efforts will serve as a reference to orient researchers and system designers in this area.
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Wireless Sensor Networks (WSN) are being used for a number of applications involving infrastructure monitoring, building energy monitoring and industrial sensing. The difficulty of programming individual sensor nodes and the associated overhead have encouraged researchers to design macro-programming systems which can help program the network as a whole or as a combination of subnets. Most of the current macro-programming schemes do not support multiple users seamlessly deploying diverse applications on the same shared sensor network. As WSNs are becoming more common, it is important to provide such support, since it enables higher-level optimizations such as code reuse, energy savings, and traffic reduction. In this paper, we propose a macro-programming framework called Nano-CF, which, in addition to supporting in-network programming, allows multiple applications written by different programmers to be executed simultaneously on a sensor networking infrastructure. This framework enables the use of a common sensing infrastructure for a number of applications without the users having to worrying about the applications already deployed on the network. The framework also supports timing constraints and resource reservations using the Nano-RK operating system. Nano- CF is efficient at improving WSN performance by (a) combining multiple user programs, (b) aggregating packets for data delivery, and (c) satisfying timing and energy specifications using Rate- Harmonized Scheduling. Using representative applications, we demonstrate that Nano-CF achieves 90% reduction in Source Lines-of-Code (SLoC) and 50% energy savings from aggregated data delivery.
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We present an algorithm for bandwidth allocation for delay-sensitive traffic in multi-hop wireless sensor networks. Our solution considers both periodic as well as aperiodic real-time traffic in an unified manner. We also present a distributed MAC protocol that conforms to the bandwidth allocation and thus satisfies the latency requirements of realtime traffic. Additionally, the protocol provides best-effort service to non real-time traffic. We derive the utilization bounds of our MAC protocol.
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Knowing exactly where a mobile entity is and monitoring its trajectory in real-time has recently attracted a lot of interests from both academia and industrial communities, due to the large number of applications it enables, nevertheless, it is nowadays one of the most challenging problems from scientific and technological standpoints. In this work we propose a tracking system based on the fusion of position estimations provided by different sources, that are combined together to get a final estimation that aims at providing improved accuracy with respect to those generated by each system individually. In particular, exploiting the availability of a Wireless Sensor Network as an infrastructure, a mobile entity equipped with an inertial system first gets the position estimation using both a Kalman Filter and a fully distributed positioning algorithm (the Enhanced Steepest Descent, we recently proposed), then combines the results using the Simple Convex Combination algorithm. Simulation results clearly show good performance in terms of the final accuracy achieved. Finally, the proposed technique is validated against real data taken from an inertial sensor provided by THALES ITALIA.