987 resultados para boundary detection


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Wind power has become one of the popular renewable resources all over the world and is anticipated to occupy 12% of the total global electricity generation capacity by 2020. For the harsh environment that the wind turbine operates, fault diagnostic and condition monitoring are important for wind turbine safety and reliability. This paper employs a systematic literature review to report the most recent promotions in the wind turbine fault diagnostic, from 2005 to 2012. The frequent faults and failures in wind turbines are considered and different techniques which have been used by researchers are introduced, classified and discussed.

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In this paper, a polynomial time algorithm is presented for solving the Eden problem for graph cellular automata. The algorithm is based on our neighborhood elimination operation which removes local neighborhood configurations which cannot be used in a pre-image of a given configuration. This paper presents a detailed derivation of our algorithm from first principles, and a detailed complexity and accuracy analysis is also given. In the case of time complexity, it is shown that the average case time complexity of the algorithm is \Theta(n^2), and the best and worst cases are \Omega(n) and O(n^3) respectively. This represents a vast improvement in the upper bound over current methods, without compromising average case performance.

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Current approaches to airport development and land use sit at odds with the tradition of airports as spaces for aviation (Stevens et a/. 2010). While airports remain the primary interface between air transport and society, the functions they include within their boundaries have expanded well beyond the provision of infrastructure for aviation and logistics. Shopping malls, commercial office space, hotels, golf courses and conference facilities arc increasingly normal uses of land within airport boundaries (Kasarda 2008), and enhance the role of airports from transport infrastructure to a new form of economic infrastructure (Freestone 2009). However, the expanding role of airports, and the resulting diversification in airport land uses, has not been without opposition.

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This project was a step forward in developing intrusion detection systems in distributed environments such as web services. It investigates a new approach of detection based on so-called "taint-marking" techniques and introduces a theoretical framework along with its implementation in the Linux kernel.

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Industry-school partnerships (ISPs) are increasingly being recognised as a new way of providing vocational education opportunities. However, there is limited research investigating their impact on school to work transitions. This paper reports on a government-led ISP, the Gateway to Industry Schools Program, established in Queensland, Australia. Central to this initiative is the Queensland Minerals and Energy Academy (QMEA), a lead organisation for 28 schools and 17 multi-national sponsor companies. This research adopted a qualitative case study methodology and draws upon boundary crossing theory as means to understand a Minerals and Energy ISP. We distinguish four types of boundary crossing mechanisms, which align with principles for effectiveness in ISPs. The main findings were that boundary crossing mechanisms assist ISPs to develop industry-based contextualised curriculum and to prepare school students for employment.

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This paper elaborates the approach used by the Applied Data Mining Research Group (ADMRG) for the Social Event Detection (SED) Tasks of the 2013 MediaEval Benchmark. We extended the constrained clustering algorithm to apply to the first semi-supervised clustering task, and we compared several classifiers with Latent Dirichlet Allocation as feature selector in the second event classification task. The proposed approach focuses on scalability and efficient memory allocation when applied to a high dimensional data with large clusters. Results of the first task show the effectiveness of the proposed method. Results from task 2 indicate that attention on the imbalance categories distributions is needed.

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The microstructure of an artificial grain boundary in an YBa2Cu3O7-δ (YBCO) thin film grown on a (100)(110), [001]-tilt yttria-stabilized-zirconia (YSZ) bicrystal substrate has been studied using transmission electron microscopy (TEM). The orientation relationship between the YBCO film and the YSZ substrate was [001]YBCO∥[001]YSZ and [110]YBCO∥[100]YSZ for each half of the bicrystal film. However, the exact boundary geometry of the bicrystal substrate was not transferred to the film. The substrate boundary was straight while the film boundary was wavy. In several cases there was bending of the lattice confined within a distance of a few basal-plane lattice spacings from the boundary plane and microfaceting. No intergranular secondary phase was observed but about 25% of the boundary was covered by c-axis-tilted YBCO grains and a-axis-oriented grains, both of which were typically adjacent to CuO grains or surrounded by a thin Cu-rich amorphous layer.

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Weak links were fabricated by pulsed laser deposition of YBa 2Cu3Ox thin films on Y-ZrO2 bicrystal substrates. They were formed by transferring the bicrystal boundary into the epitaxial film during the film growth. Their properties were determined by the misorientation angle ( theta ) between the two halves of the bicrystal. The transport properties of the weak links were studied as a function of theta and an exponential dependence of the weak link critical current density was observed for angles up to 45 degrees . Clear Josephson effects with good microwave and magnetic field response were observed.

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Engineered grain boundary Josephson junctions in YBaCuO were formed on bicrystal Y-ZrO2 substrates. Laser deposited films were patterned into micron size microbridges. The authors obsd. a pronounced correlation between superconducting transport properties of grain boundary junctions and the misorientation angle θ between the two halves of the bicrystal. The crit. Josephson current Ic decreased about four orders of magnitude as θ was increased from 0 to 45 degrees. Clear microwave and magnetic field responses were obsd. at 77 K. At this temp., crit. current times normal resistance products, IcRn, of up to 1 mV were measured for low angle grain boundaries, and Shapiro steps were obsd. up to that voltage. DC SQUIDs were fabricated, and best performance at 77 K was obtained for θ = 32° with a 4-μm strip width. To utilize the higher IcRn value of a lower θ, submicron junctions have to be developed. [on SciFinder(R)]

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The assessment of choroidal thickness from optical coherence tomography (OCT) images of the human choroid is an important clinical and research task, since it provides valuable information regarding the eye’s normal anatomy and physiology, and changes associated with various eye diseases and the development of refractive error. Due to the time consuming and subjective nature of manual image analysis, there is a need for the development of reliable objective automated methods of image segmentation to derive choroidal thickness measures. However, the detection of the two boundaries which delineate the choroid is a complicated and challenging task, in particular the detection of the outer choroidal boundary, due to a number of issues including: (i) the vascular ocular tissue is non-uniform and rich in non-homogeneous features, and (ii) the boundary can have a low contrast. In this paper, an automatic segmentation technique based on graph-search theory is presented to segment the inner choroidal boundary (ICB) and the outer choroidal boundary (OCB) to obtain the choroid thickness profile from OCT images. Before the segmentation, the B-scan is pre-processed to enhance the two boundaries of interest and to minimize the artifacts produced by surrounding features. The algorithm to detect the ICB is based on a simple edge filter and a directional weighted map penalty, while the algorithm to detect the OCB is based on OCT image enhancement and a dual brightness probability gradient. The method was tested on a large data set of images from a pediatric (1083 B-scans) and an adult (90 B-scans) population, which were previously manually segmented by an experienced observer. The results demonstrate the proposed method provides robust detection of the boundaries of interest and is a useful tool to extract clinical data.

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A nanostructured gold surface consisting of closely packed outwardly growing spikes is investigated for the electrochemical detection of dopamine and cytochrome c. A significant electrocatalytic effect for the electrooxidation of both dopamine and ascorbic acid at the nanostructured electrode was found due to the presence of surface active sites which allowed the detection of dopamine in the presence of excess ascorbic acid to be achieved by differential pulse voltammetry. By simple modification with a layer of Nafion, the enhanced electrocatalytic properties of the nanostructured surface was maintained while increasing the selectivity of dopamine detection in the presence of interfering species such as excess ascorbic and uric acids. Also, upon modification of the nanostructured surface with a monolayer of cysteine, the electrochemical response of immobilised cytochrome c in two distinct conformations was observed. This opens up the possibility of using such a nanostructured surface for the characterisation of other biomolecules and in bio-electroanalytical applications.

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Stress corrosion cracking (SCC) is a well known form of environmental attack in low carat gold jewellery. It is desirable to have a quick, easy and cost effective way to detect SCC in alloys and prevent them from being used and later failing in their application. A facile chemical method to investigate SCC of 9 carat gold alloys is demonstrated. It involves a simple application of tensile stress to a wire sample in a corrosive environment such as 1–10 % FeCl3 which induces failure in less than 5 minutes. In this study three quaternary (Au, Ag, Cu and Zn) 9 carat gold alloy compositions were investigated for their resistance to SCC and the relationship between time to failure and processing conditions is studied. It is envisaged that the use of such a rapid and facile screening procedure at the production stage may readily identify alloy treatments that produce jewellery that will be susceptible to SCC in its lifetime.

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This paper presents a new framework for distributed intrusion detection based on taint marking. Our system tracks information flows between applications of multiple hosts gathered in groups (i.e., sets of hosts sharing the same distributed information flow policy) by attaching taint labels to system objects such as files, sockets, Inter Process Communication (IPC) abstractions, and memory mappings. Labels are carried over the network by tainting network packets. A distributed information flow policy is defined for each group at the host level by labeling information and defining how users and applications can legally access, alter or transfer information towards other trusted or untrusted hosts. As opposed to existing approaches, where information is most often represented by two security levels (low/high, public/private, etc.), our model identifies each piece of information within a distributed system, and defines their legal interaction in a fine-grained manner. Hosts store and exchange security labels in a peer to peer fashion, and there is no central monitor. Our IDS is implemented in the Linux kernel as a Linux Security Module (LSM) and runs standard software on commodity hardware with no required modification. The only trusted code is our modified operating system kernel. We finally present a scenario of intrusion in a web service running on multiple hosts, and show how our distributed IDS is able to report security violations at each host level.

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This paper presents an investigation into event detection in crowded scenes, where the event of interest co-occurs with other activities and only binary labels at the clip level are available. The proposed approach incorporates a fast feature descriptor from the MPEG domain, and a novel multiple instance learning (MIL) algorithm using sparse approximation and random sensing. MPEG motion vectors are used to build particle trajectories that represent the motion of objects in uniform video clips, and the MPEG DCT coefficients are used to compute a foreground map to remove background particles. Trajectories are transformed into the Fourier domain, and the Fourier representations are quantized into visual words using the K-Means algorithm. The proposed MIL algorithm models the scene as a linear combination of independent events, where each event is a distribution of visual words. Experimental results show that the proposed approaches achieve promising results for event detection compared to the state-of-the-art.

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OBJECTIVES: To provide an overview of 1) traditional methods of skin cancer early detection, 2) current technologies for skin cancer detection, and 3) evolving practice models of early detection. DATA SOURCES: Peer-reviewed databased articles and reviews, scholarly texts, and Web-based resources. CONCLUSION: Early detection of skin cancer through established methods or newer technologies is critical for reducing both skin cancer mortality and the overall skin cancer burden. IMPLICATIONS FOR NURSING PRACTICE: A basic knowledge of recommended skin examination guidelines and risk factors for skin cancer, traditional methods to further examine lesions that are suspicious for skin cancer and evolving detection technologies can guide patient education and skin inspection decisions.