415 resultados para Equivalent network


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In this paper we present a novel platform for underwater sensor networks to be used for long-term monitoring of coral reefs and �sheries. The sensor network consists of static and mobile underwater sensor nodes. The nodes communicate point-to-point using a novel high-speed optical communication system integrated into the TinyOS stack, and they broadcast using an acoustic protocol integrated in the TinyOS stack. The nodes have a variety of sensing capabilities, including cameras, water temperature, and pressure. The mobile nodes can locate and hover above the static nodes for data muling, and they can perform network maintenance functions such as deployment, relocation, and recovery. In this paper we describe the hardware and software architecture of this underwater sensor network. We then describe the optical and acoustic networking protocols and present experimental networking and data collected in a pool, in rivers, and in the ocean. Finally, we describe our experiments with mobility for data muling in this network.

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Islanded operation, protection, reclosing and arc extinguishing are some of the challenging issues related to the connection of converter interfaced distributed generators (DGs) into a distribution network. The isolation of upstream faults in grid connected mode and fault detection in islanded mode using overcurrent devices are difficult. In the event of an arc fault, all DGs must be disconnected in order to extinguish the arc. Otherwise, they will continue to feed the fault, thus sustaining the arc. However, the system reliability can be increased by maximising the DG connectivity to the system: therefore, the system protection scheme must ensure that only the faulted segment is removed from the feeder. This is true even in the case of a radial feeder as the DG can be connected at various points along the feeder. In this paper, a new relay scheme is proposed which, along with a novel current control strategy for converter interfaced DGs, can isolate permanent and temporary arc faults. The proposed protection and control scheme can even coordinate with reclosers. The results are validated through PSCAD/EMTDC simulation and MATLAB calculations.

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Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.

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We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships.

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As the acceptance and popularity of wireless networking technologies has proliferated, the security of the IEEE 802.11 wireless local area network (WLAN) has advanced in leaps and bounds. From tenuous beginnings, where the only safe way to deploy a WLAN was to assume it was hostile and employ higherlayer information security controls, to the current state of the art, all manner of improvements have been conceived and many implemented. This work investigates some of the remaining issues surrounding IEEE 802.11 WLAN operation. While the inherent issues in WLAN deployments and the problems of the original Wired Equivalent Privacy (WEP) provisions are well known and widely documented, there still exist a number of unresolved security issues. These include the security of management and control frames and the data link layer protocols themselves. This research introduces a novel proposal to enhance security at the link layer of IEEE 802.11 WLANs and then conducts detailed theoretical and empirical investigation and analysis of the eects of such proposals. This thesis �rst de�nes the state of the art in WLAN technology and deployment, including an overview of the current and emerging standards, the various threats, numerous vulnerabilities and current exploits. The IEEE 802.11i MAC security enhancements are discussed in detail, along with the likely outcomes of the IEEE 802.11 Task Group W1, looking into protected management frames. The problems of the remaining unprotected management frames, the unprotected control frames and the unprotected link layer headers are reviewed and a solution is hypothesised, to encrypt the entire MAC Protocol Data Unit (MPDU), including the MAC headers, not just the MAC Service Data Unit (MSDU) commonly performed by existing protocols. The proposal is not just to encrypt a copy of the headers while still using cleartext addresses to deliver the frame, as used by some existing protocols to support the integrity and authenticity of the headers, but to pass the entire MPDU only as ciphertext to also support the con�dentiality of the frame header information. This necessitates the decryption of every received frame using every available key before a station can determine if it is the intended recipient. As such, this raises serious concerns as to the viability of any such proposal due to the likely impact on throughput and scalability. The bulk of the research investigates the impacts of such proposals on the current WLAN protocols. Some possible variations to the proposal are also provided to enhance both utility and speed. The viability this proposal with respect to the eect on network throughput is then tested using a well known and respected network simulation tool, along with a number of analysis tools developed speci�cally for the data generated here. The simulator's operation is �rst validated against recognised test outputs, before a comprehensive set of control data is established, and then the proposal is tested and and compared against the controls. This detailed analysis of the various simulations should be of bene�t to other researchers who need to validate simulation results. The analysis of these tests indicate areas of immediate improvement and so the protocols are adjusted and a further series of experiments conducted. These �nal results are again analysed in detail and �nal appraisals provided.