84 resultados para network-based intrusion detection system
Resumo:
Unmanned surface vehicles are becoming increasingly vital tools in a variety of maritime applications. Unfortunately, their usability is severely constrained by the lack of a reliable obstacle detection and avoidance system. In this article, one such experimental platform is proposed, which performs obstacle detection, risk assessment and path planning (avoidance) tasks autonomously in an integrated manner. The detection system is based on a vision-LIDAR (light detection and ranging) system, whereas a heuristic path planner is utilised. A unique property of the path planner is its compliance with the marine collision regulations. It is demonstrated through hardware-in-the-loop simulations that the proposed system can be useful for both uninhabited and manned vessels.
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In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events; however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly
auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.
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This paper investigates camera control for capturing bottle cap target images in the fault-detection system of an industrial production line. The main purpose is to identify the targeted bottle caps accurately in real time from the images. This is achieved by combining iterative learning control and Kalman filtering to reduce the effect of various disturbances introduced into the detection system. A mathematical model, together with a physical simulation platform is established based on the actual production requirements, and the convergence properties of the model are analyzed. It is shown that the proposed method enables accurate real-time control of the camera, and further, the gain range of the learning rule is also obtained. The numerical simulation and experimental results confirm that the proposed method can not only reduce the effect of repeatable disturbances but also non-repeatable ones.
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Residual recipient haematopoietic cells may coexist with donor haemopoietic tissue following BMT. This is known as mixed chimaerism. The incidence of mixed chimaerism varies with the sensitivity of the detection system used; DNA based methodologies are the most sensitive. The influence of mixed chimaerism on leukaemia relapse and graft rejection is unclear. The lineages in which mixed chimaerism occurs may affect outcome.
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The increasing scale of Multiple-Input Multiple- Output (MIMO) topologies employed in forthcoming wireless communications standards presents a substantial implementation challenge to designers of embedded baseband signal processing architectures for MIMO transceivers. Specifically the increased scale of such systems has a substantial impact on the perfor- mance/cost balance of detection algorithms for these systems. Whilst in small-scale systems Sphere Decoding (SD) algorithms offer the best quasi-ML performance/cost balance, in larger systems heuristic detectors, such Tabu-Search (TS) detectors are superior. This paper addresses a dearth of research in architectures for TS-based MIMO detection, presenting the first known realisations of TS detectors for 4 × 4 and 10 × 10 MIMO systems. To the best of the authors’ knowledge, these are the largest single-chip detectors on record.
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Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.
Resumo:
Indoor wireless network based client localisation requires the use of a radio map to relate received signal strength to specific locations. However, signal strength measurements are time consuming, expensive and usually require unrestricted access to all parts of the building concerned. An obvious option for circumventing this difficulty is to estimate the radio map using a propagation model. This paper compares the effect of measured and simulated radio maps on the accuracy of two different methods of wireless network based localisation. The results presented indicate that, although the propagation model used underestimated the signal strength by up to 15 dB at certain locations, there was not a signigicant reduction in localisation performance. In general, the difference in performance between the simulated and measured radio maps was around a 30 % increase in rms error
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We address the issue of autonomic management in hierarchical component-based distributed systems. The long term aim is to provide a modelling framework for autonomic management in which QoS goals can be defined, plans for system adaptation described and proofs of achievement of goals by (sequences of) adaptations furnished. Here we present an early step on this path. We restrict our focus to skeleton-based systems in order to exploit their well-defined structure. The autonomic cycle is described using the Orc system orchestration language while the plans are presented as structural modifications together with associated costs and benefits. A case study is presented to illustrate the interaction of managers to maintain QoS goals for throughput under varying conditions of resource availability.
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Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context.
Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing.
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We consider two different approaches to describe the formation of social networks under mutual consent and costly communication. First, we consider a network-based approach; in particular Jackson–Wolinsky’s concept of pairwise stability. Next, we discuss a non-cooperative game-theoretic approach, through a refinement of the Nash equilibria of Myerson’s consent game. This refinement, denoted as monadic stability, describes myopically forward looking behavior of the players. We show through an equivalence that the class of monadically stable networks is a strict subset of the class of pairwise stable networks that can be characterized fully by modifications of the properties defining pairwise stability.
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Inorganic polyphosphate (polyP) is increasingly being recognized as an important phosphorus sink within the environment, playing a central role in phosphorus exchange and phosphogenesis. Yet despite the significant advances made in polyP research there is a lack of rapid and efficient analytical approaches for the quantification of polyP accumulation in microbial cultures and environmental samples. A major drawback is the need to extract polyP from cells prior to analysis. Due to extraction inefficiencies this can lead to an underestimation of both intracellular polyP levels and its environmental pool size: we observed 23-58% loss of polyP using standard solutions and current protocols. Here we report a direct fluorescence based DAPI assay system which removes the requirement for prior polyP extraction before quantification. This increased the efficiency of polyP detection by 28-55% in microbial cultures suggesting quantitative measurement of the intracellular polyP pool. It provides a direct polyP assay which combines quantification capability with technical simplicity. This is an important step forward in our ability to explore the role of polyP in cellular biology and biogeochemical nutrient cycling.
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The Gray Laboratory charged-particle microbeam has been used to assess the clonogenic ability of Chinese hamster V79 cells after irradiation of their nuclei with a precisely defined number of protons with energies of 1.0 and 3.2 MeV. The microbeam uses a 1-mum. silica capillary collimator to deliver protons to subcellular targets with high accuracy. The detection system is based on a miniature photomultiplier tube positioned above the cell dish, which detects the photons generated by the passage of the charged particles through an 18-mum-thick scintillator placed below the cells. With this system, a detection efficiency of greater than 99% is achieved. The cells are plated on specially designed dishes (3-mum-thick Mylar base), and the nuclei are identified by fluorescence microscopy. After an incubation period of 3 days, the cells are revisited individually to assess the formation of colonies from the surviving cells. For each energy investigated, the survival curve obtained for the microbeam shows a significant deviation below I Gy from a response extrapolated using the LQ model for the survival data above 1 Gy. The data are well fitted by a model that supports the hypothesis that radioresistance is induced by low-dose hypersensitivity. These studies demonstrate the potential of the microbeam for performing studies of the effects of single charged particles on cells in vitro. The hypersensitive responses observed are comparable with those reported by others using different radiations and techniques. (C) 2001 by Radiation Research Society.
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A novel Networks-on-Chip (NoC) router architecture specified for FPGA based implementation with configurable Virtual-Channel (VC) is presented. Each pipeline stage of the proposed architecture has been optimized so that low packet propagation latency and reduced hardware overhead can be achieved. The proposed architecture enables high performance and cost effective VC NoC based on-chip system interconnects to be deployed on FPGA.
Resumo:
Data flow techniques have been around since the early '70s when they were used in compilers for sequential languages. Shortly after their introduction they were also consideredas a possible model for parallel computing, although the impact here was limited. Recently, however, data flow has been identified as a candidate for efficient implementation of various programming models on multi-core architectures. In most cases, however, the burden of determining data flow "macro" instructions is left to the programmer, while the compiler/run time system manages only the efficient scheduling of these instructions. We discuss a structured parallel programming approach supporting automatic compilation of programs to macro data flow and we show experimental results demonstrating the feasibility of the approach and the efficiency of the resulting "object" code on different classes of state-of-the-art multi-core architectures. The experimental results use different base mechanisms to implement the macro data flow run time support, from plain pthreads with condition variables to more modern and effective lock- and fence-free parallel frameworks. Experimental results comparing efficiency of the proposed approach with those achieved using other, more classical, parallel frameworks are also presented. © 2012 IEEE.
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A proof-of-concept study was reported on analysis of antigen–antibody recognition based on resonant Rayleigh scattering response of single Au nanoparticles in an imaging chamber. As benefited by a traditional dark-field microscope and a spectrograph, individual Au nanoparticles (30 nm) were observed with high signal-to-noise ratio and they were effectively utilized to monitor changes in refractive index induced by specific binding of the adsorbates. Using PSA antigen as a model, a LSPR ?max shift of about 2.85 nm was recorded for a molecular binding corresponding to 0.1 pg ml-1 of the protein biomarker. This result successfully demonstrates a non-labeling detection system for proteins as well as thousands of different chemical or biological species, and it possesses a great potential as a sensitive, on-chip and multiplexing detection.