Modelling conditional probability distributions for periodic variables

Most of the common techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce two novel techniques for tackling such problems, and investigate their performance using synthetic data. We then apply these techniques to the problem of extracting the distribution of wind vector directions from radar scatterometer data gathered by a remote-sensing satellite.

Modelling conditional probability distributions for periodic variables

Most of the common techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we apply two novel techniques to the problem of extracting the distribution of wind vector directions from radar catterometer data gathered by a remote-sensing satellite.

Modelling conditional probability distributions for periodic variables

Most conventional techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce three related techniques for tackling such problems, and investigate their performance using synthetic data. We then apply these techniques to the problem of extracting the distribution of wind vector directions from radar scatterometer data gathered by a remote-sensing satellite.

Estimating conditional probability densities for periodic variables

Most of the common techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we introduce three novel techniques for tackling such problems, and investigate their performance using synthetic data. We then apply these techniques to the problem of extracting the distribution of wind vector directions from radar scatterometer data gathered by a remote-sensing satellite.

Probability distribution modelling to improve stability in nonlinear MIMO control

We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.

Risk-based maintenance model for offshore oil and gas pipelines:a case study

Offshore oil and gas pipelines are vulnerable to environment as any leak and burst in pipelines cause oil/gas spill resulting in huge negative Impacts on marine lives. Breakdown maintenance of these pipelines is also cost-intensive and time-consuming resulting in huge tangible and intangible loss to the pipeline operators. Pipelines health monitoring and integrity analysis have been researched a lot for successful pipeline operations and risk-based maintenance model is one of the outcomes of those researches. This study develops a risk-based maintenance model using a combined multiple-criteria decision-making and weight method for offshore oil and gas pipelines in Thailand with the active participation of experienced executives. The model's effectiveness has been demonstrated through real life application on oil and gas pipelines in the Gulf of Thailand. Practical implications. Risk-based inspection and maintenance methodology is particularly important for oil pipelines system, as any failure in the system will not only affect productivity negatively but also has tremendous negative environmental impact. The proposed model helps the pipelines operators to analyze the health of pipelines dynamically, to select specific inspection and maintenance method for specific section in line with its probability and severity of failure.

Breakdown of plant cell biomass by filamentous fungi

Three species of filamentous fungi, Botrytis cinerea, Sporotrichum thermophile and Trichoderma viride, have been selected to assess the potential of utilizing filamentous fungi to degrade plant cell biomass produced by mass cell culture techniques. All three fungal species grew comparatively well on plant cell biomass with no requirement for supplementary nutrients. Of the three species assessed B. cinerea demonstrated the most growth. This species also produced the greatest yield of D-glucose. However, when culture conditions were modified, yields of D-glucose were markedly reduced indicating that the combination of species and culture conditions must be thoroughly investigated to ensure maximum product yield. The growth of filamentous fungi on plant cells also markedly affected the nature of the resulting fungal-plant cell residue, increasing the levels of soluble carbohydrates and essential amino acids with the largest increase in these materials being promoted by B. cinerea.

Mechanisms for triggering high-voltage breakdown in vacuum

The electrical and optical characteristics of a cylindrical alumina insulator (94% Al203) have been measured under ultra-high vacuum (P < 10-8 mBar) conditions. A high-resolution CCD camera was used to make real-time optical recordings of DC prebreakdown luminescence from the ceramic, under conditions where DC current magnitudes were limited to less than 50μA. Two concentric metallized rings formed a pair of co-axial electrodes, on the end-face of the alumina tube; a third 'transparent' electrode was employed to study the effect of an orthogonal electric field upon the radial conduction processes within the metallized alumina specimen. The wavelength-spectra of the emitted light was quantified using a high-speed scanning monochromator and photo-multiplier tube detector. Concurrent electrical measurements were made alongside the recording of optical-emission images. An observed time-dependence of the photon-emission is correlated with a time-variation observed in the DC current-voltage characteristics of the alumina. Optical images were also recorded of pulsed-field surface-flashover events on the alumina ceramic. An intensified high-speed video technique provided 1ms frames of surface-flashover events, whilst 100ns frames were achieved using an ultra high-speed fast-framing camera. By coupling this fast-frame camera to a digital storage oscilloscope, it was possible to establish a temporal correlation between the application of a voltage-pulse to the ceramic and the evolution of photonic emissions from the subsequent surface-flashover event. The electro-optical DC prebreakdown characteristics of the alumina are discussed in terms of solid-state photon-emission processes, that are believed to arise from radiative electron-recombination at vacancy-defects and substitutional impurity centres within the surface-layers of the ceramic. The physical nature of vacancy-defects within an alumina dielectric is extensively explored, with a particular focus placed upon the trapped electron energy-levels that may be present at these defect centres. Finally, consideration is given to the practical application of alumina in the trigger-ceramic of a sealed triggered vacuum gap (TVG) switch. For this purpose, a physical model describing the initiation of electrical breakdown within the TVG regime is proposed, and is based upon the explosive destabilisation of trapped charge within the alumina ceramic, triggering the onset of surface-flashover along the insulator. In the main-gap prebreakdown phase, it is suggested that the electrical-breakdown of the TVG is initiated by the low-field 'stripping' of prebreakdown electrons from vacancy-defects in the ceramic under the influence of an orthogonal main-gap electric field.

The breakdown of plant cell biomass by fungi

Three species of fungi Sporotrichum thermophile, Botrytis cinerea and Trichoderma viride were assessed for their ability to utilize a variety of plant cell substrates (methanol extracted), Catharanthus roseus, Daucus carota, re-autoclaved C. roseus, re-autoclaved D. carota) which preliminary studies had indicated contained the necessary nutrients for fungal growth. Incubated in a suitable manner all three fungal species were able to grow on C. roseus and D. carota plant cell biomass in addition to material which had undergone methanol extraction or a re-autoclaving process to remove soluble components. Fungal biomass yields were markedly influenced by substrate, with each fungal species demonstrating a preference for particular plant cell material. Incubation conditions i.e. static or shaken and temperature also proved important. Release of glucose (i.e. values higher than Day 0) promoted by fungal breakdown of plant cell biomass was only noted with methanol extracted, re-autoclaved C. roseus and re-autoclaved D. carota material. A re-autoclaved substrate was also generally associated with high fungal C1, Cx, B-glucosidase and endo-polygalacturonase activity. In addition for each enzyme highest values were usually obtained from a particular fungal species. Buffering cultures at pH 3 or 5 further influenced enzyme activity, however in a majority of cases when flasks were unbuffered and the pH rose naturally to alkaline values higher enzyme activity was recorded. Likewise Tween 80 addition had only a limited beneficial effect. Finally filtrates containing glucose produced both from the re-autoclaving process and through fungal activity on plant cell biomass were utilized for Fusarium oxysporum, Saccharomyces cerevisiae and C. roseus plant cell culture. Although reasonable fungal biomass was obtained the use of such filtrates proved unsuitable for plant cell growth.

The breakdown of stainless steels in strong acids

A study was made of the corrosion behaviour in the ASTM standard Nitric acid and Oxalic acid tests, of two commercial AISI type 304L steels in the as received condition and after various heat treatments. Optical microscopy and SEM, TEM and STEM in conjunction with energy dispersive x-ray analysis, were used to correlate the corrosion behaviour of these steels with their microstructure. Some evidence of phosphorus segregation at grain boundaries was found. The corrosion behaviour at microstructural level was studied by examining on the TEM thin foils of steel that had been exposed to boiling nitric acid. Banding attack in the nitric acid and oxalic acid tests was studied using SEM and EPNA and found to be due to the micro-segregation of chromium and nickel. Using two experimental series of 304L, one a 17% Cr, 91 Ni, steel with phosphorus additions from 0.006% to 0.028%, the other a 20% Cr, 121 Ni steel with boron additions from 0.0011 to 0.00B51. The effect of these elements on corrosion in the nitric acid test was studied. The effect of different cooling rates and different solution treatment temperature on the behaviour of these steels was examined. TEM and STEM in conjunction with energy-dispersive x-ray analysis were again used to study the microstructure of the steels. Phosphorus was found to affect the corrosion behaviour but no effect was found with boron.

Asymptotically exact probability distribution for the Sinai model with finite drift

We obtain the exact asymptotic result for the disorder-averaged probability distribution function for a random walk in a biased Sinai model and show that it is characterized by a creeping behavior of the displacement moments with time, similar to v(mu n), where mu <1 is dimensionless mean drift. We employ a method originated in quantum diffusion which is based on the exact mapping of the problem to an imaginary-time Schrodinger equation. For nonzero drift such an equation has an isolated lowest eigenvalue separated by a gap from quasicontinuous excited states, and the eigenstate corresponding to the former governs the long-time asymptotic behavior.

High speed electrical breakdown mechanisms in gaseous, liquid and solid dielectric materials

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